'The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell'

Michael Truell: ...

迈克尔·特鲁尔：...

our goal with Cursor is to invent a new type of programming, a very different way to build software.

我们的 Cursor 目标是发明一种新型编程，一种非常不同的软件构建方式。

So a world kind of after code, I think that more and more being an engineer will start to feel like being a logic designer, and really, it will be about specifying your intent for how exactly you want everything to work.

因此，在代码之后的世界中，我认为越来越多的工程师将开始感觉自己像逻辑设计师，而且实际上，这将是关于指定您希望一切如何准确工作的意图。

Lenny Rachitsky: What is the most counter-intuitive thing you've learned so far about building Cursor?

Lenny Rachitsky：到目前为止，关于构建 Cursor，您学到的最违反直觉的事情是什么？

Michael Truell: We definitely didn't expect to be doing any of our own model development.

Michael Truell：我们绝对没想到要进行任何我们自己的模型开发。

And at this point, every magic moment in Cursor involves a custom model in some way.

此时，Cursor 中的每个神奇时刻都以某种方式涉及自定义模型。

Lenny Rachitsky: What's something that you wish you knew before you got into this role?

Lenny Rachitsky：在担任这个角色之前，您希望了解什么？

Michael Truell: Many people you hear hire too fast, I think we actually hired too slow to begin with.

Michael Truell：你听到的很多人招聘速度太快，我认为我们实际上一开始招聘速度就太慢了。

Lenny Rachitsky: You guys went from $0 to 100 million ARR in a year and a half, which is historic.

Lenny Rachitsky：你们在一年半的时间里将 ARR 从 0 美元增加到了 1 亿美元，这是历史性的。

Was there an inflection point where things just started to really take off?

是否有一个拐点让事情才刚刚开始真正起飞？

Michael Truell: The growth has been fairly just consistent on an exponential.

Michael Truell：增长在指数上相当一致。

And exponential to begin with feels fairly slow when the numbers are really low, and it didn't really show off to the races to begin with.

当数字非常低时，指数一开始感觉相当慢，并且一开始并没有真正向比赛展示。

Lenny Rachitsky: What do you think is the secret to your success?

Lenny Rachitsky：您认为您成功的秘诀是什么？

Lenny Rachitsky: Today, my guest is Michael Truell.

莱尼·拉奇茨基：今天，我的客人是迈克尔·特鲁尔。

Michael is co-founder and CEO of Anysphere, the company behind Cursor.

Michael 是 Cursor 背后的公司 Anysphere 的联合创始人兼首席执行官。

If you've been living under a rock and haven't heard of Cursor, it is the leading AI code editor, and is at the very forefront of changing how engineers and product teams build software.

如果您一直生活在岩石下并且没有听说过 Cursor，那么它是领先的 AI 代码编辑器，并且处于改变工程师和产品团队构建软件方式的最前沿。

It's also one of the fastest growing products of all time, hitting 100 million ARR just 20 months after launching, and then 300 million ARR just two years since launch.

它也是有史以来增长最快的产品之一，在推出仅 20 个月后，ARR 就达到了 1 亿，而在推出后仅仅两年，ARR 就达到了 3 亿。

Lenny Rachitsky: Michael's been working on AI for 10 years.

Lenny Rachitsky：Michael 从事人工智能研究已经 10 年了。

He studied computer science and math at MIT, did AI research at MIT and Google, and is a student of tech and business history.

他在麻省理工学院学习计算机科学和数学，在麻省理工学院和谷歌进行人工智能研究，并且是技术和商业史的学生。

As you'll soon see, Michael thinks deeply about where things are heading, and what the future of building software looks like.

正如您很快就会看到的那样，Michael 深入思考了事情的发展方向以及构建软件的未来。

We chat about the origin story of Cursor, his prediction of what happens after code, his biggest counter-intuitive lessons from building Cursor, where he sees things going for software engineers, and so much more.

我们讨论了 Cursor 的起源故事、他对代码后发生的事情的预测、他从构建 Cursor 中获得的最大的反直觉的教训、他对软件工程师的看法等等。

Lenny Rachitsky: Michael does not do many podcasts.

Lenny Rachitsky：迈克尔做的播客不多。

The only other podcast he's ever done is Lex Fridman, so it was a true honor to have Michael on.

他唯一做过的播客是莱克斯·弗里德曼 (Lex Fridman)，所以迈克尔能参加是我的荣幸。

If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube.

如果您喜欢这个播客，请不要忘记订阅并在您最喜欢的播客应用程序或 YouTube 中关注它。

Also, if you become an annual subscriber of my newsletter, you get a year free of Perplexity, Linear, Superhuman, Notion, and Granola.

另外，如果您成为我的时事通讯的年度订阅者，您将获得一年免费的 Perplexity、Linear、Super human、Notion 和 Granola。

Check it out at lennysnewsletter.com, and click bundle.

请访问 lennysnewsletter.com 进行查看，然后单击“捆绑”。

With that, I bring you Michael Truell.

接下来，我为您带来迈克尔·特鲁尔。

Lenny Rachitsky: This episode is brought to you by Eppo.

Lenny Rachitsky：本集由 Eppo 为您带来。

Eppo is a next-generation A/B testing and feature management platform built by alums of Airbnb and Snowflake for modern growth teams.

Eppo 是由 Airbnb 和 Snowflake 的校友为现代增长团队构建的下一代 A/B 测试和功能管理平台。

Companies like Twitch, Miro, ClickUp, and DraftKings rely on Eppo to power their experiments.

Twitch、Miro、ClickUp 和 DraftKings 等公司依靠 Eppo 来支持他们的实验。

Experimentation is increasingly essential for driving growth, and for understanding the performance of new features, and Eppo helps you increase experimentation velocity, while unlocking rigorous deep analysis in a way that no other commercial tool does.

实验对于推动增长和了解新功能的性能越来越重要，Eppo 可以帮助您提高实验速度，同时以其他商业工具无法做到的方式解锁严格的深度分析。

Lenny Rachitsky: When I was at Airbnb, one of the things that I loved most was our experimentation platform, where I could set up experiments easily, troubleshoot issues, and analyze performance all on my own.

Lenny Rachitsky：当我在 Airbnb 时，我最喜欢的事情之一就是我们的实验平台，在这里我可以轻松地设置实验、解决问题并自行分析性能。

Eppo does all that and more, with advanced statistical methods that can help you shave weeks off experiment time, an accessible UI for diving deeper into performance, and out-of-the-box reporting that helps you avoid annoying, prolonged analytics cycles.

Eppo 做到了这一切，甚至更多，先进的统计方法可以帮助您缩短数周的实验时间，可访问的用户界面可以更深入地了解性能，开箱即用的报告可以帮助您避免烦人的、延长的分析周期。

Eppo also makes it easy for you to share experiment insights with your team, sparking new ideas for the A/B testing flywheel.

Eppo 还使您可以轻松地与您的团队分享实验见解，激发 A/B 测试飞轮的新想法。

Eppo powers experimentation across every use case, including product, growth, machine learning, monetization, and email marketing.

Eppo 为每个用例提供实验支持，包括产品、增长、机器学习、货币化和电子邮件营销。

Check out Eppo at geteppo.com/lenny, and 10X your experiment velocity.

请访问 geteppo.com/lenny 查看 Eppo，将您的实验速度提高 10 倍。

That's getE-P-P-O.com/lenny.

那是 getE-P-P-O.com/lenny。

Lenny Rachitsky: This episode is brought to you by Vanta.

Lenny Rachitsky：本集由 Vanta 为您带来。

When it comes to ensuring your company has top-notch security practices, things get complicated fast.

当谈到确保您的公司拥有一流的安全实践时，事情很快就会变得复杂。

Now, you can assess risk, secure the trust of your customers, and automate compliance for SOC 2, ISO 27001, HIPAA, and more with a single platform, Vanta.

现在，您可以使用单一平台 Vanta 评估风险、确保客户的信任并自动实现 SOC 2、ISO 27001、HIPAA 等的合规性。

Vanta's market-leading trust management platform helps you continuously monitor compliance, alongside reporting and tracking risk.

Vanta 市场领先的信任管理平台可帮助您持续监控合规性，同时报告和跟踪风险。

Plus, you can save hours by completing security questionnaires with Vanta AI.

此外，您还可以通过 Vanta AI 完成安全调查问卷来节省时间。

Join thousands of global companies that use Vanta to automate evidence collection, unify risk management, and streamline security reviews.

加入数千家使用 Vanta 自动化证据收集、统一风险管理和简化安全审查的全球公司行列。

Get $1,000 off Vanta when you go to vanta.com/lenny.

访问vanta.com/lenny，可享受 Vanta 立减 1,000 美元的优惠。

That's V-A-N-T-A.com/lenny.

那是 V-A-N-T-A.com/lenny。

Lenny Rachitsky: Michael, thank you so much for being here.

Lenny Rachitsky：迈克尔，非常感谢你来到这里。

Welcome to the podcast.

欢迎来到播客。

Michael Truell: Thank you.

迈克尔·特鲁尔：谢谢。

It's great to be here.

很高兴来到这里。

Thank you for having me.

谢谢你有我。

Lenny Rachitsky: When we were chatting earlier, you had this really interesting phrase, this idea of what comes after code.

Lenny Rachitsky：当我们之前聊天时，你有一个非常有趣的短语，这个关于代码之后会发生什么的想法。

Talk about that, just the vision you have of where you think things are going in terms of moving from code to maybe something else.

谈论这个，只是你对从代码转向其他东西方面的​​事情进展的看法。

Michael Truell: Our goal with Cursor is to invent sort of a new type of programming, a very different way to build software, that's kind of just distilled down into you describing the intent to the computer for what you want in the most concise way possible, and really distilled down to just defining how you think the software should work, and how you think it should look.

Michael Truell：我们对 Cursor 的目标是发明一种新型编程，一种非常不同的软件构建方式，这种方式只是提炼为你以最简洁的方式向计算机描述你想要的意图，并且真正提炼为定义你认为软件应该如何工作，以及你认为它应该如何外观。

With the technology that we have today, and as it matures, we think you can get to a place where you can invent a new method of building software that's higher level, and more productive, in some cases, more accessible too.

凭借我们今天拥有的技术，随着它的成熟，我们认为您可以发明一种新的软件构建方法，这种方法更高水平、更高效，在某些情况下也更易于访问。

Michael Truell: And that process will be a gradual moving away from what building software looks like today.

Michael Truell：这个过程将逐渐远离当今构建软件的样子。

I want to contrast it with maybe the vision of what software looks like in the future that I think...

我想将它与我认为的未来软件的愿景进行对比......

A couple of visions that are in a popular consciousness that we at least have some disagreement with.

我们至少有一些不同意的观点。

One is, there's a group of people who think that software building in the future is going to look very much like it does today, which mostly means text editing, formal programming languages, like TypeScript, and Go, and C, and Rust.

其一，有一群人认为未来的软件构建将与今天非常相似，这主要意味着文本编辑、正式编程语言，如 TypeScript、Go、C 和 Rust。

And then there's another group that kind of thinks you're just going to type into a bot, and you're going to ask it to build you something, and then you're going to ask it to change something about what you're building, and it's kind of like this chatbot, Slackbot style where you're talking to your engineering department.

还有另一群人认为你只需向机器人输入内容，然后你会要求它为你构建一些东西，然后你会要求它改变你正在构建的东西，这有点像这个聊天机器人，Slackbot 风格，你可以在其中与你的工程部门交谈。

Michael Truell: And we think that there are problems with both of those visions.

Michael Truell：我们认为这两种愿景都存在问题。

I think that on the chatbot style end of things...

我认为在聊天机器人风格的事情上......

And we think it's going to look weirder than both.

我们认为它看起来会比两者都更奇怪。

The problem with the chatbot style end of things is that lacks a lot of precision.

聊天机器人风格的问题在于缺乏很多精确性。

If you want humans to have complete control over what the software looks like, and how it works, you need to let them gesture at what they want to be changed in a form factor that's more precise than just, "Change this about my app." In a text box, removed from the whole thing.

如果您希望人们能够完全控制软件的外观及其工作原理，您需要让他们以比仅仅“更改我的应用程序的这一点”更精确的形式来表达他们想要更改的内容。在文本框中，从整个内容中删除。

And then the version of the world where nothing changes we think is wrong, because we think the technology is going to get much, much, much better.

然后，我们认为没有任何变化的世界版本是错误的，因为我们认为技术会变得越来越好。

Michael Truell: And so a world after code, I think that it looks like a world where you have a representation of the logic of your software that does look more like English, you have written down...

Michael Truell：因此，在代码之后的世界，我认为它看起来像是一个软件逻辑表示的世界，它看起来更像英语，你已经写下了......

You can imagine in form, you can imagine in kind of an evolution of programming language towards pseudocode.

你可以想象形式，你可以想象编程语言向伪代码的演变。

You have written down the logic of the software, and you can edit that at a high level, and you can point at that.

你已经写下了软件的逻辑，你可以在高层次上编辑它，你可以指出它。

And it won't be the impenetrable millions of lines of code, it'll instead be something that's much Terser, and easier to understand, easier to navigate.

它不会是难以理解的数百万行代码，而是更简洁、更容易理解、更容易导航的东西。

But that world where the kind of crazy, hard to understand symbols start to evolve towards something that's a little bit more human-readable, and human-editable, is one that we're working towards.

但是，那种疯狂的、难以理解的符号开始演变为更易于人类阅读和编辑的世界，正是我们正在努力实现的目标。

Lenny Rachitsky: This is a profound point.

Lenny Rachitsky：这是一个深刻的观点。

I want to make sure people don't miss what you're saying here, which is that what you're envisioning in the next year essentially is kind of when things start to shift, is, people move away from even seeing code, having to think in code in JavaScript and Python, and there's this abstraction that will appear, essentially pseudocode, describing what the code should be doing more in English sentences.

我想确保人们不会错过你在这里所说的内容，即你所设想的明年基本上是当事情开始发生变化时，人们甚至不再看代码，而不得不用 JavaScript 和 Python 的代码进行思考，并且将会出现这种抽象，本质上是伪代码，描述代码应该用英语句子做更多的事情。

Michael Truell: Yep.

迈克尔·特鲁尔：是的。

We think it ends up looking like that, and we're very opinionated that that path goes through existing professional engineers, and it looks like this evolution away from code.

我们认为它最终看起来像那样，而且我们非常固执地认为这条路径要经过现有的专业工程师，而且看起来像是远离代码的演变。

And it definitely looks like the human still being in the driver's seat, and the human having both a ton of control over all aspects of the software and not giving that up.

看起来人类仍然坐在驾驶座上，并且人类对软件的各个方面都有大量的控制权，并且不会放弃这一点。

And then also the human having the ability to make changes very quickly, having a fast duration loop and not just having something in the background that's super slow and takes weeks, go do all your work for you.

然后，人类也有能力非常快速地进行更改，具有快速的持续时间循环，而不仅仅是在后台有一些超级慢且需要数周时间的东西，为您完成所有工作。

Lenny Rachitsky: This begs the question for people that are currently engineers, or thinking about becoming engineers, or designers, or product manager, what skills do you think will be more and more valuable in this world of what comes after code?

Lenny Rachitsky：这给目前担任工程师或正在考虑成为工程师、设计师或产品经理的人们提出了一个问题，您认为在这个编码之后的世界中，哪些技能将变得越来越有价值？

Michael Truell: I think taste will be increasingly more valuable.

Michael Truell：我认为品味会越来越有价值。

And I think often when people think about tastes in the realm of software, they think about visuals, or taste over smooth animations, and coloring things, UI, UX, et cetera on the visual design of things.

我认为，当人们考虑软件领域的品味时，他们通常会考虑视觉效果，或者对流畅的动画、色彩、UI、UX 等视觉设计的品味。

And the visual side of things is an important part of defining a piece of software, but then, as mentioned before, I think that the other half of defining a piece of software is the logic of it, and how the thing works.

事物的视觉方面是定义一个软件的重要部分，但是，正如前面提到的，我认为定义一个软件的另一半是它的逻辑，以及它是如何工作的。

Michael Truell: And we have amazing tools for specing out the visuals of things, and then when you get into the logic of how a piece of software works, really, the best representation we have of that is code right now.

Michael Truell：我们拥有令人惊叹的工具来指定事物的视觉效果，然后当您了解软件如何工作的逻辑时，实际上，我们现在拥有的最好的表示就是代码。

You can kind of gesture at it with Figma, and you can gesture at it with writing down notes, but it's when you have an actual working prototype.

你可以用 Figma 来对它做手势，也可以通过写下笔记来对它做手势，但前提是你有一个实际的工作原型。

And so I think that more and more, being an engineer will start to feel like being a logic designer, and really, it will be about specifying your intent for how exactly you want everything to work.

因此，我认为，越来越多地，作为一名工程师将开始感觉像作为一名逻辑设计师，实际上，这将是关于明确你希望一切如何准确工作的意图。

It'd be more about the whats, and a little bit less about how exactly you're going to do things under the hood.

更多的是关于“是什么”，而不是关于你将如何在幕后做事。

Michael Truell: I think taste will be increasingly important.

Michael Truell：我认为品味将会变得越来越重要。

I think one aspect of software engineering, and we're very far from this right now, and there are lots of funny memes going around the internet about some of the trials and tribulations people can run into if they trust AI for too many things that comes to engineering, around building apps that have glaring deficiencies, and problems, and functionality issues.

我认为软件工程的一个方面，我们现在离这一点还很远，互联网上有很多有趣的模因，关于人们如果在工程方面信任人工智能太多的事情，围绕构建具有明显缺陷、问题和功能问题的应用程序，可能会遇到的一些考验和磨难。

But I think we will get to a place where you'll be able to be less careful as a software engineer, which, right now, is an incredibly, incredibly important skill.

但我认为我们将达到这样一个境界，作为一名软件工程师，你将能够不那么小心，而这在目前是一项非常非常重要的技能。

We'll move a little bit from carefulness, and a little bit more towards taste.

我们将从谨慎转向品味。

Lenny Rachitsky: This makes me think of vibe coding, is that kind of what you're describing when you talk about not having to think about the details as much, and just kind of going with the flow?

Lenny Rachitsky：这让我想到了氛围编码，当你谈论不必过多考虑细节，而只是随波逐流时，这就是你所描述的吗？

Michael Truell: I think it's related.

迈克尔·特鲁尔：我认为这是相关的。

I think that vibe coding right now describes exactly this state of creation that is pretty controversial, where you're generating a lot of coding, you aren't really understanding the details.

我认为现在的氛围编码准确地描述了这种非常有争议的创作状态，您生成了大量编码，但您并没有真正理解细节。

That is a state of creation that then has lots of problems, you don't really...

这是一种存在很多问题的创造状态，你真的...

By not understanding the details under the hood right now, you then very quickly get to a place where you're kind of limited at a certain point, where you create something that's big enough that you can't change.

如果现在不了解幕后的细节，那么你很快就会陷入在某个点上受到限制的地方，在那里你创建的东西足够大以至于你无法改变。

And so I think some of the ideas that we're interested around, how do you give people continued control over all the details when they don't really understand the code?

因此，我认为我们感兴趣的一些想法是，当人们并不真正理解代码时，如何让他们继续控制所有细节？

I think that solutions there are very relevant to the people who are vibe coding right now.

我认为那里的解决方案与现在进行氛围编码的人非常相关。

I think that right now, we lack the ability to let the tastemakers actually have complete control over the software.

我认为现在我们缺乏让时尚引领者真正完全控制软件的能力。

One of the issues also with vibe coding, and letting taste really shine through from people is, you can create stuff, but a lot of it the AI making decisions that are unwieldy and you don't have to control over.

氛围编码以及让品味真正从人们身上散发出来的问题之一是，你可以创造东西，但其中很多是人工智能做出的决定是笨拙的，你不需要控制。

Lenny Rachitsky: One more question along these lines.

Lenny Rachitsky：还有一个问题。

You threw out this word taste.

你把味道这个词扔掉了。

When you say taste, what are you thinking?

当你说味道时，你在想什么？

Michael Truell: I'm thinking having the right idea for what should be built.

Michael Truell：我认为对于应该构建什么有正确的想法。

It will become more and more about effortless translation of, here's exactly what you want built, here's how you want everything to work, here's how you want it to look.

它将变得越来越轻松地翻译，这正是您想要构建的，这就是您希望一切工作的方式，这就是您希望它的外观。

And then you'll be able to make that on a computer, and it will less be about this kind of translation layer of, you and your team have a picture of what you'd want to build, and then you have to really painstakingly, labor-intensive, lay out that into a format that a computer can then execute and interpret.

然后你就可以在计算机上实现它，而不再是这种翻译层，你和你的团队对你想要构建的东西有了一个了解，然后你必须非常艰苦地、劳动密集型地将其布置成计算机可以执行和解释的格式。

I think less than the UI side of things, maybe taste is a little bit of a misnomer, but just about having the right idea for what should be built.

我认为，除了 UI 方面之外，品味可能有点用词不当，但只是对应该构建的内容有正确的想法。

Lenny Rachitsky: Awesome.

莱尼·拉奇茨基：太棒了。

Okay.

好的。

I'm going to come back to these topics, but I want to actually zoom us back out to the beginnings of Cursor.

我将回到这些主题，但我实际上想把我们拉回 Cursor 的开头。

I have never heard the origin story, I don't think many people know how this whole thing started.

我从未听说过起源故事，我想很多人都不知道这整件事是如何开始的。

Basically you guys are building one of the fastest growing products in the history of the world, it's changing the way people build products, it's changing careers, professions, it's changing so much.

基本上，你们正在构建世界历史上增长最快的产品之一，它正在改变人们构建产品的方式，它正在改变职业、专业，它正在改变如此之多。

How did it all begin?

这一切是如何开始的？

Any memorable moments along the journey of the early days?

早期的旅程中有哪些难忘的时刻？

Michael Truell: Cursor kind of started as a solution search of a problem, and a little bit where it very much came from reflecting on how AI was going to get better over the course of the next 10 years.

Michael Truell：Cursor 最初是作为对问题的解决方案搜索而开始的，很大程度上来自于对人工智能在未来 10 年中将如何变得更好的反思。

There were kind of two defining moments, one was being really excited by using the first beta version of Code Pilot, actually.

有两个决定性的时刻，一个是使用 Code Pilot 的第一个测试版时感到非常兴奋。

This was the first time we had used an AI product that was really, really, really useful, and was actually just useful at all, and wasn't just a vaporware kind of demo thing.

这是我们第一次使用真正非常非常有用的人工智能产品，而且实际上只是有用，而不仅仅是一种汽件式的演示产品。

Michael Truell: And in addition to being the first AI product that we'd use that was useful, Code Pilot was also one of the most useful, if not the most useful dev tool we'd ever adopted, and that got us really excited.

Michael Truell：除了是我们使用的第一个有用的人工智能产品之外，Code Pilot 也是我们采用过的最有用的开发工具之一（如果不是最有用的话），这让我们非常兴奋。

Another moment that got us really excited was the series of scaling on papers coming out of OpenAI and other places that showed that even if we had no new ideas, AI was going to get better and better just by pulling on simple levers, like scaling up the models, and also scaling up the data that was going into the models.

另一个让我们非常兴奋的时刻是来自 OpenAI 和其他地方的一系列论文的扩展，这些论文表明，即使我们没有新的想法，人工智能也会变得越来越好，只需拉动简单的杠杆，比如扩展模型，以及扩展进入模型的数据。

Michael Truell: And so at the end of 2021, beginning of 2022, this got us excited about how AI products were now possible, this technology was going to mature into the future.

Michael Truell：因此，在 2021 年底、2022 年初，这让我们对人工智能产品现在如何成为可能感到兴奋，这项技术将在未来走向成熟。

And it felt like when we looked around, there were lots of people talking about making models, and it felt like people weren't really picking an area of knowledge work and thinking about what it was going to look like as AI got better and better.

当我们环顾四周时，感觉有很多人在谈论制作模型，而且感觉人们并没有真正选择一个知识工作领域，也没有思考随着人工智能变得越来越好，它会是什么样子。

And that set us on the path to an idea generation exercise, it was like, "How are these areas of knowledge work going to change in the future as this tech gets more mature?

这让我们走上了创意生成练习的道路，就像是，“随着这项技术变得更加成熟，这些知识工作领域在未来将如何变化？

What is the end state of the work going to look like?

工作的最终状态会是什么样子？

How are the tools that we use to do that work going to change?

我们用来完成这项工作的工具将如何改变？

How are the models going to need to get better to support changes in the work?

模型需要如何变得更好以支持工作中的变化？

And once scaling and pre-training ran out, how are you going to keep pushing for technological capabilities?"

一旦扩展和预训练结束，你将如何继续推动技术能力？”

Michael Truell: And the misstep at the beginning of Cursor is we actually worked on...

Michael Truell：Cursor 一开始的失误是我们实际上致力于......

We sort of did this whole grand exercise, and we decided to work on an area of knowledge work that we thought would be relatively uncompetitive, and sleepy, and boring, and no one would be looking at it, because we thought, "Oh, coding's great, coding's totally going to change with this AI, but people are already doing that." So there was a period of four months to begin with, where we were actually working on a very different idea, which was helping to automate and augment mechanical engineering, and building tools for mechanical engineers.

我们完成了整个伟大的练习，我们决定从事一个我们认为相对没有竞争力、昏昏欲睡、无聊的知识工作领域，没有人会关注它，因为我们想，“哦，编码很棒，编码完全会随着人工智能而改变，但人们已经在这样做了。”因此，一开始有四个月的时间，我们实际上正在研究一个非常不同的想法，这有助于自动化和增强机械工程，并为机械工程师构建工具。

Michael Truell: There were problems from the get-go in that.

Michael Truell：从一开始就存在问题。

Me and my co-founders, we weren't mechanical engineers.

我和我的联合创始人都不是机械工程师。

We had friends who were mechanical engineers, but we were very much unfamiliar with the field.

我们有机械工程师的朋友，但我们对这个领域非常陌生。

So there was a little bit of a blind man and the elephant problem from the get-go.

所以从一开始就存在一些盲人摸象的问题。

There were problems around, how would you actually take the models that exist to today and make them useful for mechanical engineering?

存在一些问题，您将如何实际利用当今存在的模型并使它们对机械工程有用？

The way we netted out is, you need to actually develop your own models from the get-go.

我们得出的结论是，您需要从一开始就实际开发自己的模型。

And the way we did that was tricky, and there's not a lot of data on the internet of 3D models of different tools and parts, and the steps that I expect to build up to those 3D models, and then getting them from the sources that have them is also a tricky process too.

我们这样做的方式很棘手，互联网上没有大量不同工具和零件的 3D 模型的数据，我期望构建这些 3D 模型的步骤，然后从拥有它们的来源获取它们也是一个棘手的过程。

Michael Truell: But eventually what happened was, we came to our senses, we realized we're not super excited about mechanical engineering, it's not the thing we want to dedicate our lives to.

Michael Truell：但最终发生的事情是，我们醒悟过来，我们意识到我们对机械工程并不是非常感兴趣，这不是我们想要奉献一生的事情。

And we looked around, and in the area of programming, it felt like despite a decent amount of time ensuing, not much has changed, and it felt like the people that were working on the space maybe had a disconnect with us, and it felt like they weren't being sufficiently ambitious about where everything was going to go in the future, and how all of software creation was going to blow through these models.

我们环顾四周，在编程领域，感觉尽管接下来有相当长的时间，但并没有太大变化，感觉在这个领域工作的人们可能与我们脱节，感觉他们对未来一切的发展方向以及所有软件创建将如何突破这些模型没有足够的雄心。

And that's what set us off on the path to building Cursor.

这就是我们踏上构建 Cursor 之路的原因。

Lenny Rachitsky: Okay.

莱尼·拉奇茨基：好的。

So interesting.

太有趣了。

Okay, so first of all, I love that...

好吧，首先，我喜欢...

This is advice that you often hear of go after a boring industry because no one's going to be there, and there's opportunity.

这是你经常听到的建议，去追求一个无聊的行业，因为没有人会去那里，但那里有机会。

And sometimes it works, but I love that in this journey, it's like, "No, actually, go after the hottest, most popular space, AI coding, app building." And it worked out.

有时它会起作用，但我喜欢在这个旅程中，就像，“不，实际上，追求最热门、最受欢迎的空间、人工智能编码、应用程序构建。”结果成功了。

And the way you phrased it just now is, you didn't see enough ambition potentially, that you thought there was more to be done.

你刚才的措辞是，你没有看到足够的潜在雄心，你认为还有更多的事情要做。

So it feels like that's an interesting lesson.

所以感觉这是一堂有趣的课。

Even if something looks like, "Okay, it's too late, there's GitHub, Code Pilot's out there." Some other products.

即使有些内容看起来像“好吧，已经太晚了，GitHub 和 Code Pilot 就在那里。”其他一些产品。

If you notice that they're just not as ambitious as they could be, or as you are, or you see almost a flaw in their approach, that there's still a big opportunity.

如果你发现他们并没有像你那样雄心勃勃，或者你发现他们的方法几乎存在缺陷，那么仍然存在很大的机会。

Does that resonate?

这引起共鸣吗？

Michael Truell: That totally resonates.

迈克尔·特鲁尔：这完全引起了共鸣。

A part of it is, you need there to be leapfrogs that can happen, you need there to be things that you can do.

其中一部分是，你需要有可能发生的跨越，你需要有你可以做的事情。

And I think the exciting thing about AI is, in a bunch of places, and I think this is very much still true of our space, and can talk about how we think about that and how we deal with that, but I think that just the ceiling is really high.

我认为人工智能令人兴奋的地方在于，在很多地方，我认为这在我们的领域仍然是正确的，并且可以谈论我们如何看待这个问题以及我们如何处理这个问题，但我认为天花板确实很高。

And yes, if you look around, probably even if you take the best tool, any of these fields, there should be a lot more that needs to be done over the next few years.

是的，如果你环顾四周，可能即使你采用了最好的工具，在这些领域中的任何一个领域，在接下来的几年里都应该有更多的事情需要做。

Having that space, having that high ceiling, I think is unique amongst areas of software, at least the degree to which it is high with AI.

拥有这样的空间，拥有如此高的上限，我认为在软件领域是独一无二的，至少在人工智能方面是独一无二的。

Lenny Rachitsky: Let's come back to the IDE questions.

Lenny Rachitsky：让我们回到 IDE 问题。

So there's a few routes you could have taken, and other companies are doing different routes.

因此，您可以采取几条路线，而其他公司正在采取不同的路线。

So there's building an IDE for engineers to work within and adding AI magic to it, there's another route of just a full AI agentic dev product, and then there's just a model that is very good at coding, and focusing on building the best possible coding model.

因此，需要构建一个供工程师使用的 IDE 并为其添加 AI 魔力，还有另一种途径是提供完整的 AI 代理开发产品，然后是一个非常擅长编码的模型，并专注于构建最佳的编码模型。

What made you decide and see that the IDE path was the best route?

是什么让您决定并认为 IDE 路径是最佳路径？

Michael Truell: The folks who were from the get-go working on just a model were working on end-to-end automation programming.

Michael Truell：那些从一开始就致力于模型的人们正在致力于端到端的自动化编程。

I think they were trying to build something very different from us, which is, we care about giving humans control over all of the decisions in the end tool that they're building.

我认为他们试图构建与我们非常不同的东西，也就是说，我们关心让人类控制他们正在构建的最终工具中的所有决策。

And I think those folks were very much thinking of a future where end-to-end, the whole thing is done by AI, and maybe the AI is making all the decisions too.

我认为那些人非常想在未来，端到端，整个事情都是由人工智能完成的，也许人工智能也正在做出所有的决定。

And so, one, there was a personal interest component.

因此，第一，有个人兴趣的成分。

Two, I think that always, we've tried to be intense realists about where the technology is today, very, very, very excited about how AI is going to mature over the course of many decades.

第二，我认为我们一直努力对当今技术的现状保持强烈的现实主义者的态度，对人工智能在未来几十年内将如何成熟感到非常、非常、非常兴奋。

But I think that sometimes people...

但我认为有时人们...

There's an instinct to see AI do magical things in one area, and then kind of anthropomorphize these models, and think it's better than a smart person here, and so it must be better than a smart person there.

人们有一种本能，看到人工智能在某个领域做出神奇的事情，然后将这些模型拟人化，并认为它比这里的聪明人更好，所以它一定比那里的聪明人更好。

Michael Truell: But these things have massive issues, and we...

迈克尔·特鲁尔：但是这些事情有很大的问题，我们......

From the very start, our product development process was really about dogfooding, and using the tool intensely every day.

从一开始，我们的产品开发过程实际上就是进行测试，并每天大量使用该工具。

And we never wanted to ship anything that wasn't useful to us, and we had the benefit of doing that because we were the end users part of our product.

我们从来不想运送任何对我们无用的东西，这样做有好处，因为我们是产品的最终用户。

And I think that that instills a realism in you around where the tech is right now, and so that definitely made us think that we need the humans to be in the driver's seat, the AI cannot do everything.

我认为这会向你灌输现实主义，围绕目前的技术现状，这肯定会让我们认为我们需要人类坐在驾驶座上，人工智能不能做所有事情。

We're also interested in giving humans that control too for personal reasons, and so that gets you away from just your model company that also gets you away from just this end-end stuff without the human having control.

我们也有兴趣让人类出于个人原因进行控制，这样你就可以远离你的模范公司，也可以让你远离这种没有人类控制权的最终事物。

Michael Truell: And then the way you get to an IDE versus maybe a plug-in to an existing coding environment is the belief that programming is going to flow through these models, and the active programming is going to change a lot over the course of the next few years.

Michael Truell：然后，您使用 IDE 与现有编码环境的插件的方式是相信编程将流经这些模型，并且活跃的编程将在未来几年内发生很大变化。

And that the extensibility that existing coding environments have is so, so, so limited, so if you think that the UIs may change a lot, if you think that the form factor programming is going to change a lot, necessarily need to have control over the entire application.

现有编码环境的可扩展性非常非常有限，因此如果您认为 UI 可能会发生很大变化，如果您认为外形编程会发生很大变化，则必然需要对整个应用程序进行控制。

Lenny Rachitsky: I know that you guys today have an IDE, and that's probably the bias you have of this is maybe where the future is heading, but I'm just curious, do you think a big part of the future is also going to be AI engineers that are just sitting in Slack and just doing things for you?

Lenny Rachitsky：我知道你们今天有一个 IDE，这可能就是你们对这可能是未来发展方向的偏见，但我只是很好奇，你们认为未来的很大一部分也会是坐在 Slack 中为你们做事的 AI 工程师吗？

Is that something that fits into Cursor one day?

这有一天会适合 Cursor 吗？

Michael Truell: I think you'll want the ability to move between all of these things fairly effortlessly, and sometimes I think you will want to have the thing kind of go spin off on its own for a while, and then I think you'll want the ability to pull in the AI's work, and then work with it very, very, very quickly, and then maybe have it go spin off again.

Michael Truell：我认为你会希望能够毫不费力地在所有这些事物之间移动，有时我认为你会希望让这些东西独立运行一段时间，然后我认为你会希望有能力引入人工智能的工作，然后非常、非常、非常快地使用它，然后也许让它再次分离。

And so these kind of background versus foreground form factors, I think you want that all to work well in one place.

因此，这些背景与前景的形状因素，我认为您希望所有这些都在一个地方正常工作。

And I think the background stuff, there's a segment of programming that it's especially useful for, which is type of programming tasks where it's very easy to specify exactly what you want without much description, and exactly what correctness looks like without much description.

我认为背景知识，有一部分编程特别有用，这是一种编程任务，无需太多描述就可以很容易地准确指定您想要的内容，并且无需太多描述即可准确指定正确性。

Michael Truell: Bug fixes are a great example of that, but it's definitely not all of programming.

Michael Truell：错误修复就是一个很好的例子，但这绝对不是编程的全部。

So I think that what the IDE is will totally change over time, and our approach to having our own editor was premised on, it's going to have to evolve over time.

因此，我认为 IDE 的内容将随着时间的推移而完全改变，而我们拥有自己的编辑器的方法的前提是，它必须随着时间的推移而发展。

And I think that that will both include, you can spin off things from different surface areas like Slack, or your issue tracker, or whatever it is, and I think that will also include the pane of glass that you're staring at is going to change a lot.

我认为这都包括，你可以从不同的表面区域剥离出来，比如 Slack，或者你的问题跟踪器，或者其他任何东西，我认为这还包括你所关注的玻璃面板将会发生很大的变化。

We just mostly think of an IDE as the place where you are building software.

我们主要将 IDE 视为构建软件的地方。

Lenny Rachitsky: I think something people don't talk enough about with talking about agents and all these AI engineers that are going to be doing all this stuff for you, is basically we're all becoming engineering managers, with a lot of reports that are just not that smart, and you have to do a lot of reviewing, and approving, and specifying.

Lenny Rachitsky：我认为人们在谈论代理和所有这些将为你做所有这些事情的人工智能工程师时谈论得不够多，基本上我们都成为了工程经理，有很多报告并不那么聪明，你必须做大量的审查、批准和指定。

I guess thoughts on that, and is there anything you could do to make that easier?

我想你对此有一些想法，你能做些什么来让这件事变得更容易吗？

Because that sounds really hard.

因为这听起来真的很难。

Anyone that has had a large team, being like, "Oh my god, all these junior people just checking in with me doing not high quality work over and over." It's just like, "What a life.

任何拥有大型团队的人都会说，“天哪，所有这些初级人员只是一遍又一遍地向我检查，做的工作质量不高。”就像，“多么好的生活啊。

It's going to suck."

这会很糟糕。”

Michael Truell: Yeah.

迈克尔·特鲁尔：是的。

Maybe you one-on-ones with .

也许你会与 进行一对一的交流。

Michael Truell: Yeah.

迈克尔·特鲁尔：是的。

So the customers we've seen have most success with AI I think are still fairly conservative about some of the ways in which they use this stuff.

因此，我们看到的客户在人工智能方面取得了最大的成功，我认为他们对使用这些东西的某些方式仍然相当保守。

And so I do think today, the most successful customers really lean on things like our next edit prediction, where your coding is normal, and making the next into actions you're going to do.

所以我确实认为，今天最成功的客户确实依赖于我们的下一个编辑预测之类的东西，您的编码是正常的，并将下一个变成您要做的操作。

And then they also really lean on scoping down the stuff that you're going to hand off to the bot, and for a fixed percent of your time spent reviewing code, from an agent, or from an AI overall, you could...

然后他们还真正倾向于缩小你要交给机器人的东西的范围，并且在你花在从代理或整个人工智能审查代码的固定百分比的时间里，你可以......

There's two patterns.

有两种模式。

One is, you could spend a bunch of time specifying things up front, the AI goes and works, and then you then go and review the AI's work, and then you're done.

一是，你可以花大量时间预先指定事情，人工智能开始工作，然后你去检查人工智能的工作，然后你就完成了。

That's the whole task.

这就是整个任务。

Michael Truell: Or you can really chop things up.

Michael Truell：或者你真的可以把事情分解。

So you can specify a little bit, AI writes something, review, specify a little bit, AI writes something, review.

所以你可以指定一点，人工智能写一些东西，审查，指定一点，人工智能写一些东西，审查。

Autocompletes all in the way of that spectrum.

按照该频谱的方式自动完成所有操作。

And still we see often the most successful people using these tools are chopping things up right now, and keeping things fairly .

但我们仍然经常看到使用这些工具的最成功的人正在把事情分解，并保持事情公平。

Lenny Rachitsky: That sounds less terrible.

Lenny Rachitsky：这听起来没那么可怕。

I'm glad there's a solution here.

我很高兴这里有一个解决方案。

I want to go back to you guys building Cursor for the first time.

我想回到你们第一次构建 Cursor 的话题。

What was the point where you realized this is ready?

您在什么时候意识到已经准备好了？

What was a moment of, "Okay, I think this is time to put it out there, and see what happens"?

“好吧，我想现在是时候把它放在那里了，看看会发生什么”，这是什么时刻？

Michael Truell: So when we started building Cursor, we were fairly paranoid about spinning for a while, without releasing to the world.

Michael Truell：所以当我们开始构建 Cursor 时，我们相当偏执地旋转了一段时间，而不向世界发布。

And so to begin with too, we actually...

首先，我们实际上...

The first version of Cursor was hand-rolled.

Cursor 的第一个版本是手动滚动的。

Now we use VS Code as a base, like many browsers use Chromium as a base, and hit foot off of that.

现在我们使用 VS Code 作为基础，就像许多浏览器使用 Chromium 作为基础一样，并以此为基础。

To begin with, we didn't, and built the prototype of Cursor from scratch, and that involved a lot of work.

一开始，我们没有这样做，而是从头开始构建了 Cursor 的原型，这涉及到大量的工作。

We had to build our own...

我们必须建立自己的...

There were a lot of things that go into a modern code editor, including support for many different languages, and navigation support for moving amongst the language, error tracking support for things.

现代代码编辑器包含很多功能，包括对多种不同语言的支持、在语言之间移动的导航支持、对事物的错误跟踪支持。

There's things like an integrated command line, the ability to use remote servers, the ability to connect to remote servers to view and run code.

其中包括集成命令行、使用远程服务器的能力、连接到远程服务器以查看和运行代码的能力。

And so we kind of just went on this blitz of building things incredibly quickly, building our own editor from scratch, and then also the AI components.

所以我们就以惊人的速度进行了闪电战，从头开始构建我们自己的编辑器，然后还有人工智能组件。

Michael Truell: It was after maybe five weeks that we were living on the editor full-time, and had thrown away our previous editor, and we're using a new one.

Michael Truell：大约五周后，我们全职依靠编辑器生活，并抛弃了以前的编辑器，我们正在使用一个新的编辑器。

And then once it got to a point where we found it a bit useful, then we put it in other people's hands, and had this very short beta period.

然后，一旦我们发现它有点用，我们就会把它交给其他人，并有一个非常短的测试期。

And then we launched it out to the world within a couple of months from the first line of code, I think it was probably three months.

然后我们在从第一行代码开始的几个月内向全世界推出了它，我认为可能是三个月。

And it was definitely a, "Let's just get this out to people and build in public quickly." The thing that took us by surprise is we thought we would be building for a couple hundred people for a long time.

这绝对是，“让我们把这个发布给人们并快速公开构建。”令我们惊讶的是，我们原以为我们会在很长一段时间内为几百人建造建筑。

And from the get-go, there was an immediate rush of interest, and a lot of feedback too.

从一开始，人们就立刻产生了浓厚的兴趣，也收到了很多反馈。

That was super helpful, we learned from that.

这非常有帮助，我们从中吸取了教训。

That's actually why we switched to being based off of VS Code instead of just this hand-rolled thing.

这实际上就是为什么我们转而基于 VS Code 而不仅仅是这种手工制作的东西。

A lot of that was motivated by the initial user feedback, and then had been iterating in public from there.

其中很多都是由最初的用户反馈推动的，然后从那里开始公开迭代。

Lenny Rachitsky: I like how you understated the traction that you got.

Lenny Rachitsky：我喜欢你如何低调地表达你所获得的吸引力。

I think you guys went from $0 to 100 million ARR in a year, year and a half or something like that, which is historic.

我认为你们在一年、一年半或类似的时间内从 0 美元增加到 1 亿美元，这是历史性的。

What do you think was the key to success of something like this?

您认为此类事情成功的关键是什么？

You just talked about dogfooding being a big part of it.

您刚才谈到了内部测试是其中的一个重要组成部分。

You built it in three months, that's insane.

你花了三个月就建好了它，这太疯狂了。

What do you think is the secret to your success?

您认为您成功的秘诀是什么？

Michael Truell: The three-month version wasn't very good, and so I think it's been a sustained paranoia about, there are all of these ways in which this thing could get better.

Michael Truell：三个月的版本不是很好，所以我认为这是一种持续的偏执，有所有这些方法可以让这件事变得更好。

The end goal is really to invent a very new form of programming that involves automating a lot of coding, as we know today.

正如我们今天所知，最终目标实际上是发明一种非常新的编程形式，其中涉及自动化大量编码。

And no matter where we are with Cursor, it feels like we're very, very far away from that end goal, there's always a lot to do.

无论我们与 Cursor 处于什么位置，感觉我们距离最终目标都非常非常遥远，总是有很多事情要做。

A lot of it hasn't been over rotated on that initial push, but instead is the continued evolution of the tool, and just making the tool consistently better.

其中很多内容并没有在最初的推动中过度旋转，而是工具的持续发展，并且只是使工具不断变得更好。

Lenny Rachitsky: Was there an inflection point after those three months where things just started to really take off?

Lenny Rachitsky：在这三个月之后，事情才刚刚开始真正起飞，是否有一个拐点？

Michael Truell: To be honest, it felt fairly slow to begin with, and maybe it comes from some impatience on our part.

Michael Truell：说实话，一开始感觉相当慢，也许是因为我们有些不耐烦。

I think there's the overall speed of the growth which continues to take us by surprise.

我认为整体增长速度继续让我们感到惊讶。

I think one of the things that has been most surprising too is that the growth has been fairly just consistent on an exponential, of just consistent month-over-month growth, accelerated at times by launches on our part and other things.

我认为最令人惊讶的事情之一是，增长在指数上相当一致，只是持续的逐月增长，有时由于我们的发布和其他事情而加速。

But an exponential to begin with feels fairly slow and the numbers are really low, and so it didn't really feel off to the races to begin with.

但指数一开始感觉相当慢，而且数字非常低，所以一开始就感觉不太适合比赛。

Lenny Rachitsky: To me this sounds like build it and they will come actually working.

Lenny Rachitsky：对我来说，这听起来像是构建了它，他们就会实际工作。

You guys just built an awesome product that you loved yourselves as engineers, you put it out, people just loved it, told everyone about it.

你们刚刚打造了一款很棒的产品，作为工程师，你们很喜欢这款产品，你们把它推出来，人们很喜欢它，并告诉了所有人。

Michael Truell: It being essentially all just us, the team working on the product, and making the product good in lieu of other things one could spend one's time on.

Michael Truell：本质上就是我们，团队致力于产品，并让产品变得更好，而不是人们可以花时间做的其他事情。

We definitely spent time on tons of other things, for instance, building the team was incredibly important, and doing things like support rotations are very important.

我们确实花了很多时间在其他事情上，例如，建设团队非常重要，而支持轮换等事情也非常重要。

But some of the normal things that people would maybe reach for in building the company early on, we really let those fires burn for a long time, especially when it came to things like sales and marketing.

但是人们在早期建立公司时可能会追求的一些正常的事情，我们确实让这些火焰燃烧了很长时间，特别是当涉及到销售和营销等事情时。

Michael Truell: And so just working on the product, and building a product that you like first, your team likes, and then also then adjusting it for some set of users, that can kind of sound simple, but then, as you know, it's hard to do that well.

Michael Truell：所以，只是致力于产品，首先构建一个你喜欢、你的团队喜欢的产品，然后针对某些用户进行调整，这听起来很简单，但正如你所知，很难做得很好。

And there are a bunch of different directions one could have run in, a bunch of different product directions.

人们可以选择一堆不同的方向，一堆不同的产品方向。

Michael Truell: I think focus, and strategically picking the right things to build, and prioritizing effectively is tricky.

Michael Truell：我认为专注、战略性地选择正确的东西来构建并有效地确定优先级是很棘手的。

I think another thing that's tricky about this domain is, it's kind of a new form of product building, where it's very interdisciplinary in that we are something in between a normal software company and then a foundation model company, in that we're developing a product for millions of people, and that side of things has to be excellent, but then also one important dimension of product quality is doing more and more on the science, and doing more and more on the model side of things in places where it makes sense.

我认为这个领域的另一件棘手的事情是，它是一种新的产品构建形式，它是非常跨学科的，因为我们介于普通软件公司和基础模型公司之间，因为我们正在为数百万人开发产品，这方面必须是优秀的，但产品质量的一个重要方面是在科学上做越来越多的事情，并在有意义的地方在模型方面做越来越多的事情。

And so that element of things doing that well too has been tricky.

因此，要做好这一点也很棘手。

The overall thing would note is maybe some of these things sound simple to specify, but doing them well is hard, and they're a lot of different way you can run in.

总体而言，需要注意的是，也许其中一些事情听起来很容易指定，但做好它们却很难，而且它们有很多不同的运行方式。

Lenny Rachitsky: I'm excited to have Andrew Luo joining us today.

Lenny Rachitsky：我很高兴安德鲁·罗今天加入我们。

Andrew is CEO of OneSchema, one of our podcast sponsors.

Andrew 是 OneSchema 的首席执行官，OneSchema 是我们的播客赞助商之一。

Welcome, Andrew.

欢迎，安德鲁。

Speaker 3: Thanks for having me, Lenny.

发言者 3：谢谢你邀请我，莱尼。

Great to be here.

很高兴来到这里。

Lenny Rachitsky: So what is new with OneSchema?

Lenny Rachitsky：那么 OneSchema 有哪些新功能？

I know that you work with some of my favorite companies, like Ramp, and , and Watershed.

我知道您与我最喜欢的一些公司合作，例如 Ramp、and 和 Watershed。

I heard you guys launched a new data intake product that automates the hours of manual work that teams spent importing, and mapping, and integrating CSV in Excel files?

我听说你们推出了一款新的数据获取产品，可以自动执行团队在 Excel 文件中导入、映射和集成 CSV 所需的手动工作时间？

Speaker 3: Yes.

发言者 3：是的。

So we just launched the 2.0 of OneSchema FileFeeds.

所以我们刚刚推出了 OneSchema FileFeeds 2.0。

We've rebuilt it from the ground up with AI.

我们用人工智能从头开始重建它。

We saw so many customers coming to us with teams of data engineers that struggled with the manual work required to clean messy spreadsheets.

我们看到很多客户带着数据工程师团队来到我们这里，他们在清理凌乱的电子表格所需的手动工作中遇到了困难。

FileFeeds 2.0 allows non-technical teams to automate the process of transforming CSV and Excel files with just a simple prompt.

FileFeeds 2.0 允许非技术团队通过简单的提示来自动化转换 CSV 和 Excel 文件的过程。

We support all of the trickiest file integrations, SFTP, S3, and even email.

我们支持所有最棘手的文件集成、SFTP、S3，甚至电子邮件。

Lenny Rachitsky: I can tell you that if my team had to build integrations like this, how nice would it be to take this off our roadmap and instead use something like OneSchema.

Lenny Rachitsky：我可以告诉你，如果我的团队必须构建这样的集成，那么将其从我们的路线图上删除并使用 OneSchema 之类的东西该多好。

Speaker 3: Absolutely, Lenny.

发言者 3：当然，莱尼。

We've heard so many horror stories of outages from even just a single bad record, in transactions, employee files, purchase orders, you name it.

我们听过很多因交易、员工档案、采购订单等不良记录而导致停电的恐怖故事。

Debugging these issues is often like finding a needle in a haystack.

调试这些问题通常就像大海捞针一样。

OneSchema stops any bad data from entering your system, and automatically validates your files, generating error reports with the exact issues in all bad files.

OneSchema 会阻止任何不良数据进入您的系统，并自动验证您的文件，生成错误报告，其中包含所有不良文件中的确切问题。

Lenny Rachitsky: I know that importing incorrect data can cause all kinds of pain for your customers and quickly lose their trust.

Lenny Rachitsky：我知道导入不正确的数据会给您的客户带来各种痛苦，并很快失去他们的信任。

Andrew, thank you so much for joining me.

安德鲁，非常感谢你加入我。

If you want to learn more, head on over to oneschema.co., that's oneschema.co.

如果您想了解更多信息，请访问 oneschema.co.，即 oneschema.co。

Lenny Rachitsky: What is the most counterintuitive thing you've learned so far about building Cursor, building AI products?

Lenny Rachitsky：到目前为止，关于构建 Cursor、构建人工智能产品，你学到的最违反直觉的事情是什么？

Michael Truell: I think one thing that's been counterintuitive for us, added a little bit before, but is, we definitely didn't expect to be doing any of our own model development when we started.

Michael Truell：我认为有一件事对我们来说是违反直觉的，之前补充过一点，但是，我们在开始时绝对没有想到要进行任何我们自己的模型开发。

As mentioned, when we got into this, there were companies that were immediately from the get-go going and just focusing on training model from scratch.

如前所述，当我们进入这个领域时，有些公司从一开始就立即开始关注从头开始的培训模型。

And we had done the calculation for what it to train before, and just knew that that was not going to be able to do.

我们之前已经计算过它要训练什么，只是知道那是做不到的。

And also felt a bit like focusing one's attention in the wrong area, because there were lots of amazing models out there, and why develop all this work to replicate what other players had done.

而且感觉有点像将注意力集中在错误的领域，因为那里有很多令人惊叹的模型，以及为什么要开发所有这些工作来复制其他玩家所做的事情。

Especially on the pre-training side of things, taking a neural network that knows nothing, and then teaching it the whole internet.

特别是在预训练方面，采用一个一无所知的神经网络，然后在整个互联网上教授它。

Michael Truell: And so we thought we weren't going to be doing that at all, and it seems clear to us from the start that the existing models, there were lots of things that they could be doing for us that they weren't doing, because there wasn't the right tool built for them.

Michael Truell：所以我们认为我们根本不会这样做，从一开始我们就很清楚现有模型可以为我们做很多事情，但他们没有做，因为没有为他们构建合适的工具。

In fact though, we do a ton of model development, and internally, it's a big focus for us on the hiring front, and have assembled a fantastic team there.

但事实上，我们进行了大量的模型开发，在内部，我们的重点是招聘方面，并在那里组建了一支出色的团队。

Michael Truell: And it's also been a big win on the product quality side of things for us.

Michael Truell：对于我们来说，这在产品质量方面也是一个巨大的胜利。

And at this point, every magic moment in Cursor involves a custom model in some way.

此时，Cursor 中的每个神奇时刻都以某种方式涉及自定义模型。

So that was definitely counterintuitive, and surprising, and it's been a gradual thing, where there was an initial use case for training our own model, where it really didn't make sense to use any of the biggest foundation models.

所以这绝对是违反直觉的，令人惊讶的，这是一个渐进的事情，有一个训练我们自己的模型的初始用例，使用任何最大的基础模型确实没有意义。

That was incredibly successful, moved to another use case that worked really well, and had been going from there.

这是非常成功的，转移到另一个运行良好的用例，并一直从那里开始。

And one of the helpful things in doing this sort of model development is picking your spots carefully, not trying to reinvent the wheel, not trying to focus on places, and maybe where the best foundation models are excellent, but instead kind of focusing on their weaknesses, and how you can complement them.

进行此类模型开发的一个有用的事情是仔细选择你的位置，不要试图重新发明轮子，不要试图专注于地方，也许最好的基础模型是优秀的，而是关注它们的弱点，以及如何补充它们。

Lenny Rachitsky: I think this is going to be surprising to a lot of people hearing that you have your own models.

Lenny Rachitsky：我认为很多人听到你有自己的模型都会感到惊讶。

When people talk about Cursor and all the folks in the space, they would kind of call them GPT wrappers, they're just sitting on top of ChatGPT or Sonnet.

当人们谈论 Cursor 和该领域的所有人员时，他们会称它们为 GPT 包装器，它们只是位于 ChatGPT 或 Sonnet 之上。

What you're saying is that you have your own models, talk about just the stack behind the scenes.

你所说的是你有自己的模型，只谈论幕后的堆栈。

Michael Truell: Yeah, of course.

迈克尔·特鲁尔：是的，当然。

So we definitely use the biggest foundation models a bunch of different ways, they're really important components of bringing the Cursor experience to people.

因此，我们肯定会以多种不同的方式使用最大的基础模型，它们是为人们带来光标体验的非常重要的组成部分。

The places where we use our own models, so sometimes it's to survey a use case that a foundation model wouldn't be able to serve at all for cost or speed reasons.

我们使用自己的模型的地方，因此有时需要调查基础模型因成本或速度原因而根本无法提供服务的用例。

And so one example of that is the autocomplete side of things.

一个例子就是自动完成方面。

And so this can be a little bit tricky for people who don't code to understand, but code is this weird form of work, where sometimes, really, the next 5, 10, 20, 30 minutes of your work is entirely predictable from looking over your shoulder.

因此，对于那些不会编写代码来理解的人来说，这可能有点棘手，但代码是一种奇怪的工作形式，有时，实际上，你接下来 5、10、20、30 分钟的工作完全可以通过回头看来预测。

Michael Truell: And I would contrast this with writing.

迈克尔·特鲁尔：我会将其与写作进行对比。

So writing, lots of people are familiar with Gmail's autocomplete, and the different forms of autocomplete that show up when you're trying to post text messages, or emails, or things like that.

因此，很多人都熟悉 Gmail 的自动完成功能，以及当您尝试发布短信、电子邮件或类似内容时出现的不同形式的自动完成功能。

They can only be so helpful, because often, it's just really not clear what you're going to be writing just by looking at what you've written before.

它们的帮助非常大，因为通常情况下，仅通过查看您之前写过的内容就真的不清楚您将要写什么。

But in code sometimes, when you edit a part of a code base, you're going to need to change things, and in other parts of code base, and it's entirely clear how you're going to need to change things.

但有时在代码中，当您编辑代码库的一部分时，您将需要更改某些内容，而在代码库的其他部分中，您需要如何更改内容是完全清楚的。

Michael Truell: So one core part of Cursor is this really suit to autocomplete experience, where you predict the next set of that you're going to be doing across multiple files, across multiple places within a file.

Michael Truell：Cursor 的一个核心部分是它非常适合自动完成体验，您可以在其中预测您将在多个文件、文件内多个位置执行的下一组操作。

And making models good at that use case, one, there's a speed component of, those models need to be really fast, they need to give you a completion within 300 milliseconds.

让模型擅长该用例，一是速度因素，这些模型需要非常快，它们需要在 300 毫秒内完成。

There's also this cost component of, we're running tons, and tons, and tons of molecules, every keystroke, we need to be changing our prediction for what you're going to do next.

还有这个成本部分，我们正在运行大量、大量、大量的分子，每次击键，我们都需要改变对下一步要做什么的预测。

And then it's also this really specialty use case of, you need models that are really good, not at completing the next token, just a generic tech sequence, but are really good at autocompleting a series of diffs, looking at what's changed within a code base, and then creating the next set of things that are going to change, both deleted and added and all of that, and we found a ton of success in training models specifically for that task.

然后，这也是一个非常特殊的用例，您需要非常好的模型，不是完成下一个标记，只是一个通用的技术序列，而是非常擅长自动完成一系列差异，查看代码库中发生的更改，然后创建下一组将要更改的内容，包括删除和添加等等，我们发现专门针对该任务的训练模型取得了巨大的成功。

Michael Truell: So that's a place where no foundation models are involved, it's kind of our own thing.

Michael Truell：所以这是一个不涉及基础模型的地方，这是我们自己的事情。

We don't have a lot of labeling or branding about this in the app, power is a very core part of Cursor.

我们在应用程序中没有太多关于此的标签或品牌，权力是 Cursor 的一个非常核心的部分。

And then another set of places where a user own models are to help things like Sonnet, or Gemini, or GPT, and those sit both on the inputs of those big models, and on the output.

然后，用户自己的模型的另一组地方可以帮助 Sonnet、Gemini 或 GPT 之类的东西，这些都位于这些大模型的输入和输出上。

On the input side of things, those models are searching throughout a code base, try to figure out the parts of a code base to show to one of these big models.

在输入方面，这些模型正在整个代码库中进行搜索，尝试找出代码库的各个部分以向这些大模型之一显示。

You can kind of think about this as a mini Google search that's specifically built for finding the relevant parts of the code base to show one of these big models.

您可以将其视为一个迷你 Google 搜索，专门用于查找代码库的相关部分以显示这些大型模型之一。

Michael Truell: And then on the output side of things, we take the sketches of the changes that these models are suggesting, you make with that code base.

Michael Truell：然后在输出方面，我们绘制了这些模型建议的更改的草图，您可以使用该代码库进行更改。

And then we have models that then fill in the details of, the high level thinking is done by the smartest models, they spend a few tokens on doing that, and then these smaller specialty incredibly fast models, coupled with some inference tricks, then take those high level changes and turn them actually into full code diffs.

然后我们有模型，然后填充细节，高层思维是由最聪明的模型完成的，他们花费一些代币来做这件事，然后这些较小的专业令人难以置信的快速模型，加上一些推理技巧，然后采取这些高层变化并将它们实际上变成完整的代码差异。

And so it's been super helpful for pushing on quality in places where you need a specialty task, and it's been super helpful for pushing on speed, which is such an important dimension of product quality for us too.

因此，它对于在需要特殊任务的地方提高质量非常有帮助，并且对于提高速度也非常有帮助，这对我们来说也是产品质量的一个重要方面。

Lenny Rachitsky: This is so interesting.

Lenny Rachitsky：这太有趣了。

I just had Kevin Weil on the podcast, CPO of OpenAI, and he calls this the ensemble of models, that's the same way-

我刚刚在播客中邀请了 OpenAI 的 CPO Kevin Weil，他称之为模型集合，这是同样的方式 -

Lenny Rachitsky: ...

莱尼·拉奇茨基：……

they work, to use the best feature of each one, and to your point, the cost advantages of using cheaper models.

它们的工作原理是利用每一种的最佳功能，并且就您而言，使用更便宜的型号具有成本优势。

These other models, are they based on Llama and things like that, just open source models that you guys plug into and build on?

这些其他模型是否基于 Llama 之类的东西，只是你们插入并构建的开源模型？

Michael Truell: Yeah.

迈克尔·特鲁尔：是的。

So again, we try to be very pragmatic about the place that we're going to do this work, and we don't want to reinvent the wheel.

因此，我们再次尝试对我们将要开展这项工作的地方非常务实，我们不想重新发明轮子。

And so starting from the very best pre-trained models that exist out there, often open source ones, sometimes in collaboration with these big model providers that don't share their weights out into the world, because the thing we care about last is the ability to read line by line, the matrix of weights that then go to give you a certain output.

因此，从现有的最好的预训练模型开始，通常是开源模型，有时与这些不向世界分享权重的大型模型提供商合作，因为我们最后关心的是逐行读取权重矩阵的能力，然后为您提供一定的输出。

We just care about the ability to train these things, to post-train them.

我们只关心训练这些东西以及训练后它们的能力。

And so by and large, yes, open source models, sometimes working with the closed source providers too to tune things.

总的来说，是的，开源模型有时也会与闭源提供商合作来进行调整。

Lenny Rachitsky: This leads to a discussion that a lot of AI founders always think about and investors, which is moats, and defensibility in AI.

Lenny Rachitsky：这引发了许多人工智能创始人和投资者经常思考的讨论，即人工智能的护城河和防御性。

So it feels like one is custom models, is a moat in the space.

所以感觉就像是定制模型，是空间中的护城河。

How do you just think about long-term defensibility in the space, knowing there's other folks, as you said, launching constantly trying to eat your lunch?

你如何考虑这个领域的长期防御性，因为你知道还有其他人，正如你所说，不断地试图吃掉你的午餐？

Michael Truell: I think that there are ways to build in inertia and traditional moats, but I think by and large, we're in a space where it is incumbent on us to continue to try to build the best thing, and everyone in this industry.

Michael Truell：我认为有一些方法可以建立惯性和传统的护城河，但我认为总的来说，我们所处的空间有责任继续努力打造最好的东西，以及这个行业的每个人。

And I truly just think that the ceiling is so high that no matter what entrenchment you build, you can be leapfrogged.

我真的只是认为天花板是如此之高，无论你筑起怎样的壕沟，你都可以被超越。

And I think that this resembles markets that are maybe a little bit different from normal software markets, normal enterprise markets of the past.

我认为这类似于过去的正常软件市场、正常企业市场，可能有点不同。

I think one that comes to mind is the market for search engines at the end of 1999, or at the end of the '90s and beginning of the 2000s.

我想大家首先想到的是 1999 年底，或者 90 年代末 2000 年代初的搜索引擎市场。

I think another market that comes to mind that resembles this market in many ways, it's actually just the development of the peripheral computer and many computers in the '70s, '80s, '90s.

我认为我想到的另一个市场在很多方面与这个市场相似，它实际上只是外围计算机和许多 70 年代、80 年代、90 年代计算机的发展。

Michael Truell: And I think that, yes, in each of those markets, the ceiling was incredibly high, it was possible to swish.

迈克尔·特鲁尔：我认为，是的，在每个市场中，天花板都非常高，有可能发生变化。

You could keep getting value for the incremental hour of a smart person's time, the incremental R&D dollar for a really long time, you wouldn't run out of useful things to build.

你可以不断地从聪明人的时间增量中获得价值，在很长一段时间内增加研发费用，你不会用完有用的东西来构建。

And then in search in particular, not on the computer case, adding distribution was helpful for making the product better too, in that you could tune the algorithms, you could tune the learning based off of the data and the feedback you're getting from users.

然后，特别是在搜索中，而不是在计算机案例中，添加分发也有助于使产品变得更好，因为您可以调整算法，您可以根据数据和从用户那里获得的反馈来调整学习。

And I think that all of those dynamics exist in our market too.

我认为所有这些动态也存在于我们的市场中。

And so I think maybe the sad truth for people like us, but then the amazing truth for the world is, I think that there are many leapfrogs that exist, there's more useful things to build.

所以我认为对于像我们这样的人来说也许这是一个悲伤的事实，但对于世界来说令人惊奇的事实是，我认为存在许多跨越式的发展，有更多有用的东西可以建造。

We're a long way away from where we can compete in 5, 10 years, and it's incumbent in our state to keep that going.

我们离 5 到 10 年内能够竞争的目标还有很长的路要走，我们州有责任保持这种势头。

Lenny Rachitsky: So what I'm hearing, this sounds like a lot more like a consumer sort of moat, where it's just, be the best thing consistently so that people stick with you versus creating lock-in and things like that, where they're just...

Lenny Rachitsky：所以我听到的，这听起来更像是消费者的护城河，它只是，始终如一地做到最好，这样人们就会坚持你，而不是创造锁定之类的东西，他们只是......

Like Salesforce, where it's just contracts with the entire company, and you have to use this product.

就像 Salesforce 一样，它只是与整个公司签订合同，你必须使用这个产品。

Michael Truell: Yeah.

迈克尔·特鲁尔：是的。

I think the important thing to note is, if you're in a space where you run out of useful things to do very quickly, then that's not a great situation to be in.

我认为需要注意的重要一点是，如果你所处的空间很快就没有有用的事情可做，那么这不是一个很好的情况。

But if you're in a place where big investments, and having more and more great people working on the right path can keep giving you value, then you can get these economies of scale of R&D, and you can deeply work on the technology in the right direction, and get to a place where that is defensible.

但如果你所在的地方有大量投资，并且有越来越多的优秀人才在正确的道路上工作，可以不断为你带来价值，那么你就可以获得研发的规模经济，你可以在正确的方向上深入研究技术，并达到一个可以防御的地步。

But yes, it is...

但是，是的，它是...

I think there's a consumer-like tendency to it, and I really think it's just about building the best thing possible.

我认为这有一种类似于消费者的倾向，而且我真的认为这只是为了构建尽可能最好的东西。

Lenny Rachitsky: Do you think in the future there's one winner in this space, or do you think it's going to be a world of a number of products like this?

Lenny Rachitsky：您认为未来这个领域是否只有一个赢家，或者您认为这将是一个由许多这样的产品组成的世界？

Michael Truell: I think the market is just so very big.

Michael Truell：我认为市场非常大。

You asked about the IDE thing early on, and one thing that I think a trip of some people that were thinking about the space is, they looked at the IDE market of the past 10 years, and they said, "Who's making money off of the editors?" It's this super fragmented space where everyone kind of has their own thing, with their own figuration, and there's one company that actually makes money off making great editors, but that company is only so big.

你很早就问到了 IDE 的问题，我认为一些思考这个领域的人的一件事是，他们看了过去 10 年的 IDE 市场，他们说，“谁从编辑器中赚钱？”这是一个超级分散的空间，每个人都有自己的东西，有自己的形象，而且有一家公司实际上通过培养优秀的编辑来赚钱，但那家公司只有那么大。

And then the conclusion was, it was going to look like that in the future.

然后得出的结论是，未来会是这样。

And I think that the thing that people missed was that there was only so much you could do building an editor in the 2010s for coders, and the company that made money off of editors was doing things like making it easy to navigate around a code base, and doing some error checking and type checking for things, and having good debugging tools.

我认为人们错过的一件事是，在 2010 年代，为程序员构建编辑器能做的事情就只有这么多，而从编辑器中赚钱的公司正在做一些事情，比如让代码库更容易导航，对事物进行一些错误检查和类型检查，以及拥有良好的调试工具。

Michael Truell: Which were all very useful, but I think that the set of things you can build for programmers, I think the set of things you can build for knowledge workers in many different areas just goes very far and very deep.

Michael Truell：这些都非常有用，但我认为你可以为程序员构建的一系列东西，我认为你可以为许多不同领域的知识工作者构建的一系列东西会走得很远很深。

The problem in front of all of us is the automation of a lot of busy work and knowledge work, and really changing all the areas of knowledge work in front of us to be much higher level and more productive.

我们面前的问题是大量繁忙工作和知识工作的自动化，并真正改变我们面前知识工作的所有领域，使其水平更高、生产力更高。

Michael Truell: So that was a long-winded way to say, I think the market's really, really big that we're in.

Michael Truell：所以这是一种冗长的说法，我认为我们所处的市场真的非常大。

I think it's much bigger than people have realized than the other building tools for developers in the past.

我认为它比人们过去意识到的其他开发工具要大得多。

And I think that there will be a bunch of different solutions.

我认为将会有很多不同的解决方案。

I think that there will be one company, to be determined if it's going to be us, but I do think that there will be one company that builds the general tool that builds almost all the world's software, and that will be a very, very generationally big business.

我认为将会有一家公司，待确定是否是我们，但我确实认为将会有一家公司构建通用工具，构建几乎所有世界上的软件，这将是一个非常非常大的企业。

But I think that there will be kind of niches you can occupy in doing something for a particular segment of the market, or for a very particular part of the software development life cycle.

但我认为，在为特定市场细分或软件开发生命周期的特定部分做某事时，你可以占据一些利基市场。

But the general programming shifts from just writing formal programming languages to something way higher level.

但一般编程已经从仅仅编写正式的编程语言转变为更高级别的编程语言。

This is the application you purchase and use to do that.

这是您购买并用于执行此操作的应用程序。

I think that there will be generally one winner there, and it will be a very big business.

我认为一般都会有一个赢家，而且这将是一项非常大的生意。

Lenny Rachitsky: Juicy.

莱尼·拉奇茨基：多汁。

Along those lines, it's interesting that Microsoft was actually at the center of this first, with an amazing product, amazing distribution, Copilot you said was the thing that got you over the hump of, "Wow, there could be something really big here." And it doesn't feel like they're winning, it feels like they're falling behind.

沿着这些思路，有趣的是，微软实际上是第一个的中心，拥有令人惊叹的产品、令人惊叹的发行版，你说的 Copilot 是让你克服困难的东西，“哇，这里可能有一些非常大的东西。”而且感觉他们并不赢，反而感觉他们落后了。

What do you think happened there?

你认为那里发生了什么？

Michael Truell: I think that there are specific historical reasons why Copilot might not have lived up...

迈克尔·特鲁尔（Michael Truell）：我认为 Copilot 未能实现这一目标有特定的历史原因......

So far have lived up to the expectations that some people have for it, and then I think that there are structural reasons.

到目前为止，没有辜负一些人的期望，然后我认为有结构性原因。

I think the structural reason is...

我认为结构性原因是...

And to be clear, Microsoft, in the Copilot case, obviously a big inspiration for our work, and in general, I think they do lots of awesome things, and we're users of many Microsoft products, but I think that this is a market that's not super friendly to incumbents, in that a market that's friendly to incumbents might be one where there's only so much to do, it kind of gets commoditized fairly quickly, and you can bundle that in with other products, and where the ROI between different products is quite small.

需要明确的是，在 Copilot 的案例中，微软显然对我们的工作有很大的启发，总的来说，我认为他们做了很多很棒的事情，我们是许多微软产品的用户，但我认为这是一个对现有企业不太友好的市场，因为一个对现有企业友好的市场可能是一个只有这么多事情要做的市场，它很快就会商品化，你可以将其与其他产品捆绑在一起，投资回报率在哪里不同产品之间的差异很小。

And in that case, perhaps it doesn't make sense to buy the innovative solution, it makes sense to just kind of buy the thing that's bundled in with other stuff.

在这种情况下，也许购买创新解决方案没有意义，只购买与其他东西捆绑在一起的东西才有意义。

Michael Truell: Another market that might be particularly helpful for incumbents is one where there's...

Michael Truell：另一个可能对现有企业特别有帮助的市场是……

From the get-go, you have your stuff in one place, and it's really, really excruciatingly hard to switch, and for better or for worse.

从一开始，你的东西就放在一个地方，而且无论好坏，切换起来都非常非常困难。

I think in our case, you can try out different tools, and you can decide which product you think is better.

我认为在我们的案例中，您可以尝试不同的工具，然后您可以决定您认为哪种产品更好。

And so that's not super friendly to incumbents, and that's more friendly to whoever you think is going to have the most innovative product.

因此，这对现有企业来说并不是非常友好，而对您认为将拥有最具创新性产品的任何人来说则更友好。

And then the specific historical reasons, as I understand them are the group of people that worked on the first version of Copilot have, by and large, gone on to do other things at other places.

然后，具体的历史原因，据我了解，开发 Copilot 第一个版本的一群人基本上已经在其他地方做了其他事情。

I think it's been a little hard to coordinate among all the different departments and parties that might be involved in making something like this.

我认为在可能参与制作这样的东西的所有不同部门和团体之间进行协调有点困难。

Lenny Rachitsky: I want to come back to Cursor.

Lenny Rachitsky：我想回到 Cursor。

A question I like to ask everyone that's building a tool like this, if you could sit next to every new user that uses Cursor for the first time, just whisper a couple tips in their ear to be more successful, most successful with Cursor, what would be 1 or 2 tips?

我想问每个正在构建此类工具的人一个问题，如果您可以坐在每个第一次使用 Cursor 的新用户旁边，只需在他们耳边低语一些提示，以便使用 Cursor 更成功、最成功，那么 1 或 2 个提示会是什么？

Michael Truell: I think right now, and we'd want to fix this at a product level, a lot of being successful with Cursor is kind of having a taste for what the models can do, both what complexity of a task they can handle, and how much you need to specify things to that model, but having a taste for the quality of the model, and where its gaps exist, and what it can do and what it can't.

Michael Truell：我认为现在，我们希望在产品层面解决这个问题，Cursor 的成功很大程度上在于了解模型可以做什么，它们可以处理的任务的复杂性，以及需要为该模型指定多少内容，但了解模型的质量，它存在的差距，以及它可以做什么和不能做什么。

And right now, we don't do a good job in the product of educating people around that, and maybe giving people some swim lanes, giving people some guidelines.

目前，我们在对人们进行相关教育方面做得还不够好，也许还没有为人们提供一些泳道，为人们提供一些指导方针。

Michael Truell: But to develop that taste, would give two tips.

Michael Truell：但是要培养这种品味，我会给出两个建议。

So one is, as mentioned before, would bias less toward, trying in one go to tell the model, "Hey, here's exactly what I want you to do." Then seeing the output, and then either being disappointed or accepting the entire thing for an entire big task.

因此，正如前面提到的，我们会减少偏见，尝试一次性告诉模型，“嘿，这正是我希望你做的事情。”然后看到输出，然后要么感到失望，要么接受整个大任务的整个事情。

Instead what I would do is I would chop things up into bits, and you can spend basically the same amount of time specifying things overall, but chopped up more.

相反，我会做的是将事情分成几部分，你可以花基本上相同的时间来总体上指定事情，但要分解得更多。

So you're specifying a little bit, you're getting a little bit of work, you're specifying a little bit, getting a little bit of work, and not doing as much the, "Let's write a giant thing telling the model exactly what to do." I think that will be a little bit of a recipe for disaster right now.

所以你指定了一点，你得到了一点工作，你指定了一点，得到了一点工作，而不是做那么多，“让我们写一个巨大的东西，告诉模型到底要做什么。”我认为现在这将是一场灾难。

Michael Truell: And so biasing toward chopping things up.

Michael Truell：所以偏向于把事情分解。

At the same time, and it might make sense to do this on a side project and not on your professional work, I would encourage people to, especially developers who are used to existing workflows for building software, I would encourage people to explicitly try to fall on their face, and try to discover the limits of what these models can do by being ambitious in a safe environment, like perhaps a side project, and trying to kind of go around town, use AI to the fullest.

同时，在业余项目而不是在你的专业工作中这样做可能是有意义的，我会鼓励人们，特别是习惯于构建软件的现有工作流程的开发人员，我会鼓励人们明确地尝试摔倒，并尝试通过在安全的环境中雄心勃勃（比如可能是一个业余项目）并尝试在城镇中充分利用人工智能来发现这些模型可以做到的极限。

Because a lot of the time, we run into people who haven't given the AI yet a fair shake, and are underestimating its abilities.

因为很多时候，我们遇到的人还没有对人工智能进行公平的对待，并且低估了它的能力。

So generally biasing towards chopping things up and making things smaller, but to discover the limits of what you can do there, explicitly just try to go for broke in a safe environment, and get a taste for...

因此，通常偏向于把事情切碎并把事情变得更小，但是要发现你在那里可以做的事情的局限性，明确地只是尝试在一个安全的环境中冒险，并尝试......

You might be surprised in some of the places where the model doesn't break.

您可能会对模型没有损坏的某些地方感到惊讶。

Lenny Rachitsky: What I'm essentially hearing is build a gut feeling of what the model can do, and how far it can take an idea versus just kind of guiding it along.

Lenny Rachitsky：我听到的本质上是建立对模型可以做什么的直觉，以及它可以将一个想法带到多远的程度，而不是仅仅指导它。

And I bet that you need to rebuild this gut every time there's a new model launch, when it's on...

我敢打赌，每次有新车型发布时，你都需要重建这个肠道……

I don't know, 4.0 comes out, you have to do this again.

我不知道，4.0出来了，你得再做一次。

Is that generally right?

一般来说是这样的吗？

Michael Truell: Yes.

迈克尔·特鲁尔：是的。

For the past few years, it hasn't been as big as I think the first experience people have had with some of these big models.

在过去的几年里，它并没有像人们第一次体验这些大型模型时想象的那么大。

This is also a problem we would hope to solve much better just for users, and take the burden off of them.

这也是我们希望能够更好地为用户解决的问题，减轻他们的负担。

But each of these things have slightly different quirks and different personalities.

但这些事物中的每一个都有稍微不同的怪癖和不同的个性。

Lenny Rachitsky: Along these lines, something that people are always debating tools like Cursor, are they more helpful to junior engineers, or are they more helpful to senior engineers?

Lenny Rachitsky：沿着这个思路，人们总是在争论像 Cursor 这样的工具，它们对初级工程师更有帮助，还是对高级工程师更有帮助？

Do they make senior engineers 10X better?

它们能让高级工程师的能力提高 10 倍吗？

Do they make junior engineers more like senior engineers?

它们会让初级工程师更像高级工程师吗？

Who do you think benefits most today from Cursor?

您认为今天谁从 Cursor 中受益最多？

Michael Truell: I think across the board.

迈克尔·特鲁尔：我认为是全面的。

Both of these cohorts benefit in big ways.

这两个群体都受益匪浅。

It's a little hard to say on the relative ranking.

相对排名有点难说。

I will say, they fall into different anti-patterns.

我会说，它们属于不同的反模式。

The junior engineers we see going a little too wholesale, relying on AI for everything, and we're not yet in a place where you can kind of do that end-to-end on a professional tool, working with tens, hundreds of other people within a long-lived code base.

我们看到的初级工程师有点过于批发化，一切都依赖人工智能，而我们还没有达到可以在专业工具上端到端地做到这一点的程度，在一个长期存在的代码库中与数十、数百名其他人一起工作。

And then the senior engineers...

然后高级工程师...

For many folks, it's not true for all, and we actually often...

对于许多人来说，并非所有人都如此，而且我们实际上经常......

One of the ways these tools are adopted is, there's developer experience teams within companies, often those are staffed by incredibly senior people, because often, those are people who are building tools to make the rest of the engineers within an organization more productive.

采用这些工具的方式之一是，公司内部有开发人员体验团队，通常由非常资深的人员组成，因为这些人通常正在构建工具，以提高组织内其他工程师的工作效率。

Michael Truell: And we've seen some very, very boundary pushing kind of...

Michael Truell：我们看到了一些非常非常突破边界的行为……

We've seen people who are on the front lines of really trying to adopt the technology as much as possible there.

我们看到了那些处于第一线的人们，他们真正尝试尽可能多地采用该技术。

But by and large, I would say on average, as a group, the senior engineers underrate what AI can do for them, and stick to their existing workflows.

但总的来说，我想说，平均而言，作为一个群体，高级工程师低估了人工智能可以为他们做的事情，并坚持他们现有的工作流程。

And so the relative ranking is a little hard, I think they fall into different anti-patterns, but they both, by and large, yet get big benefits with these tools.

因此，相对排名有点困难，我认为它们属于不同的反模式，但总的来说，它们都通过这些工具获得了巨大的好处。

Lenny Rachitsky: That makes absolute sense.

Lenny Rachitsky：这绝对有道理。

I love that it's two ends of the spectrum, expect too much, don't expect enough.

我喜欢它的两端，期望太多，期望不够。

It's like the three bears allegory.

这就像三只熊的寓言。

Michael Truell: Yeah.

迈克尔·特鲁尔：是的。

Maybe the sort of senior, but not staff, right in the middle.

也许是那种高级人员，但不是职员，就在中间。

Lenny Rachitsky: Interesting.

莱尼·拉奇茨基：有趣。

Okay.

好的。

Just a couple more questions.

还有几个问题。

What's something that you wish you knew before you got into this role?

在担任这个角色之前，您希望了解什么？

If you could go back to Michael at the beginning of Cursor, which was not that long ago, and you could give him some advice, what's something that you would tell him?

如果你能回到《Cursor》刚开始的时候，也就是不久前，你可以给他一些建议，你会告诉他什么？

Michael Truell: The tough thing with this is, it feels like so much of the hard-won knowledge is tacit, and a bit hard to communicate verbally.

Michael Truell：最困难的是，感觉很多来之不易的知识都是默认的，并且有点难以口头交流。

And the sad fact of life feels like for some areas of human endeavor, you kind of do need to fall on your face to...

生活中令人悲伤的事实是，对于人类努力的某些领域，你确实需要摔倒......

Either need to fall on your face to learn the correct thing, or you need to be around someone who's a great example of excellence in the thing.

要么你需要努力学习正确的东西，要么你需要身边有一个在这方面表现出色的人。

And one area where we have felt this is hiring.

我们感觉到这一点的一个领域就是招聘。

I think that we actually were...

我想我们其实是...

So we tried to be incredibly patient on the hiring front.

因此，我们在招聘方面表现得非常耐心。

Michael Truell: It was really important to us that, both for personal reasons and also for, I think actually for the company's strategy, having a world-class group of engineers and researchers to work on Cursor with us was going to be incredibly important.

Michael Truell：对我们来说非常重要的是，无论是出于个人原因，还是为了公司的战略，拥有一支世界一流的工程师和研究人员团队与我们一起开发 Cursor 将非常重要。

Also, getting people who fit...

另外，找合适的人...

A certain mix of intellectual curiosity and experimentation, because there can be so many new things we need to build.

求知欲和实验的某种结合，因为我们需要构建很多新事物。

And then also an intellectual honesty, and maybe micro-pessimism, bluntness, because if all the noise, and...

然后还有一种理智上的诚实，也许还有微悲观主义、直率，因为如果所有的噪音，以及……

Especially as the company's grown, and the business has grown, keeping a level head I think is incredibly important too.

尤其是随着公司的发展和业务的发展，我认为保持冷静的头脑也非常重要。

Michael Truell: But getting the right group of people into the company was the thing that maybe more than anything else, apart from building the product, we really, really fussed over.

Michael Truell：但是，除了构建产品之外，让合适的人加入公司可能是我们真正非常关心的事情。

We actually waited a long time to grow the team because of that.

因此，我们实际上等待了很长时间来扩大团队。

And I think that many people you hear hired too fast, think we actually hired too slow to begin with.

我认为你听到的许多人招聘得太快，认为我们实际上一开始就招聘得太慢了。

I think it could have been remedied, I think we could have been better at it.

我认为这是可以补救的，我认为我们可以做得更好。

Michael Truell: And the method of recruiting that we ended up eventually falling into and working really well for us, which isn't that novel, of going after people that we think are really world-class, and recruiting them over the course of, in some cases, many years, ended up working for us in the end, but I don't think we were very good at it to begin with.

迈克尔·特鲁尔：我们最终采用的招聘方法对我们来说非常有效，这并不是什么新鲜事，我们会寻找我们认为真正世界一流的人，并在某些情况下，在很多年的过程中招募他们，最终为我们工作，但我认为我们一开始就不太擅长。

And so I think that there were hard-won lessons around both who was the right profile, who actually made sense in that team, what did greatness look like, and then how to talk with someone about the opportunity, and get them excited if they really weren't looking for anything.

所以我认为，关于谁是合适的人选、谁在团队中真正有意义、伟大是什么样子，以及如何与某人谈论机会，以及如何让他们在他们真的不寻找任何东西的情况下让他们兴奋，这些都是来之不易的教训。

There were lots of learnings there about how to do that well, and that took us a bit of time.

关于如何做好这件事，我们学到了很多东西，这花了我们一些时间。

Lenny Rachitsky: What are some of those learnings for folks that are hiring right now?

Lenny Rachitsky：对于现在正在招聘的人来说，有哪些经验教训？

What's something you missed or learned?

你错过或学到了什么？

Michael Truell: I think to start with, maybe we actually biased a little bit too much towards looking for people who fit the archetype of well-known school, very young, had done the things that were high credential in those well-known school environments.

Michael Truell：我认为首先，也许我们实际上有点偏向于寻找符合知名学校原型的人，他们非常年轻，在那些知名学校环境中做过高资历的事情。

And actually, I think found...

事实上，我认为发现...

Were lucky early on to find fantastic people who are willing to do this with us who were later careered.

我们很幸运，很早就找到了愿意和我们一起做这件事的优秀人才，他们后来也开始了职业生涯。

I think we should kind of spent a bunch of time on maybe a little bit the wrong profile to begin with, and part of that was a seniority thing.

我认为我们应该花大量时间在可能有点错误的个人资料上，其中一部分是资历问题。

Part of that was kind of an interest and experience thing too, we have hired people who are excellent, excellent, excellent and very young, but they maybe look in some cases slightly different from being straight out of central casting.

其中一部分也是一种兴趣和经验，我们雇佣了非常优秀、非常优秀、非常年轻的人，但他们在某些情况下可能看起来与直接从中央选角出来的人略有不同。

Michael Truell: Another lesson is just, we very much evolved our interview loop, and so now, we have a hand-rolled set of interview questions, and then core our...

Michael Truell：另一个教训是，我们极大地改进了我们的面试循环，所以现在，我们有一套手卷的面试问题，然后核心我们的......

Core to how we interview too, is actually, we have people onsite for two days, and do a project with us, a work test project.

实际上，我们面试的核心也是，我们派人在现场呆两天，和我们一起做一个项目，一个工作测试项目。

And that has worked really well, that increasingly you're finding that.

这非常有效，你会越来越发现这一点。

I think how to learn about what people are interested in, and put our best foot forward, and letting them know about the opportunity when they're really not looking for anything, and have those conversations.

我认为如何了解人们感兴趣的内容，并尽最大努力，在他们实际上没有寻找任何东西时让他们知道机会，并进行这些对话。

There's definitely been...

肯定有过...

Gotten better at that over time.

随着时间的推移，这方面变得更好了。

Lenny Rachitsky: Do you have a favorite interview question that you like to ask?

Lenny Rachitsky：您有最喜欢问的面试问题吗？

Michael Truell: I think this two-day work test which we thought would not scale past a few people has had surprising staying power.

迈克尔·特鲁尔（Michael Truell）：我认为这个为期两天的工作测试，我们认为不会超出少数人的范围，但它具有令人惊讶的持久力。

And the great thing about it is, it lets someone go end-to-end on it like a real project.

它的伟大之处在于，它可以让人们像真正的项目一样进行端到端的处理。

It's not work that we use, it's canned list of projects.

我们使用的不是工作，而是预先准备好的项目列表。

But it gives you two days of seeing a real work product, and it doesn't have to be incredibly time-enhancing other teams from time.

但它让你有两天的时间看到真正的工作产品，而且它不必从时间上极大地提高其他团队的时间。

You can take the time you would spend in a half day or one day onsite, and you kind of spread it out over those two days, and give someone a lot of time to do work on their projects, and so that can actually help it scale.

您可以花半天或一天的时间在现场，然后将其分散在这两天中，并给某人很多时间来完成他们的项目，这样实际上可以帮助扩大规模。

Michael Truell: It helps to enforce, do you want to be around this person type test, because you are around this person for two days, a bunch of meals with them.

Michael Truell：这有助于强制执行，你是否想在这个人身边进行类型测试，因为你在这个人身边呆了两天，和他们一起吃了很多饭。

We didn't expect that one to stick around, but that has been really, really important to our value to process, and then also important to getting people excited at, especially the very early stages of the company.

我们没想到这个人会留下来，但这对我们的价值处理非常非常重要，而且对于让人们感到兴奋也很重要，尤其是在公司的早期阶段。

Because before, people are using the product, and know about it.

因为以前，人们正在使用该产品，并且了解它。

And when the product is comparatively not very good, really, the only thing you have going for you is a team of people that some people find special and want to be around.

当产品相对不太好时，实际上，你唯一能做的就是拥有一群人，有些人觉得他们很特别，想要和他们在一起。

And the two days would give us a chance to just have this person meet us, and in some cases, hopefully get convinced that they want to throw in with us.

这两天让我们有机会让这个人与我们见面，在某些情况下，希望能确信他们想加入我们。

That one was unexpected.

那是出乎意料的。

Not exactly an interview question, but kind of like a forward interview.

不完全是一个面试问题，但有点像前瞻性面试。

Lenny Rachitsky: The ultimate interview question.

Lenny Rachitsky：终极面试问题。

So just to be very clear about what you're describing, you give them an assignment, like, "Build this feature in our actual code base, work with the team to code it and ship it." Is that roughly right?

因此，为了非常清楚您所描述的内容，您给他们一个任务，例如“在我们的实际代码库中构建此功能，与团队合作对其进行编码并发布。”大致是这样吗？

Michael Truell: Yes.

迈克尔·特鲁尔：是的。

So we don't use the IP, not shift end-to-end, but it's like a mock...

所以我们不使用IP，不进行端到端的转移，但这就像一个模拟......

Very often in our code base, "Here's a real mini two-day project.

在我们的代码库中经常出现这样的情况：“这是一个真正的小型为期两天的项目。

You're going to do it end-to-end." Largely being left alone, there's collaboration too.

你要从头到尾地做这件事。”很大程度上是孤立的，但也有合作。

And then we're a pretty imprisoned company, in almost all cases, it's actually just sitting in office with us too.

然后我们是一家相当被囚禁的公司，几乎在所有情况下，它实际上也只是和我们一起坐在办公室里。

Lenny Rachitsky: And you've been saying that this has scaled to even today, so how big are you guys at this point?

Lenny Rachitsky：您一直在说，这种情况已经发展到今天，那么你们现在有多大呢？

Lenny Rachitsky: So small for the scale and impact.

Lenny Rachitsky：就规模和影响而言，规模太小了。

I was thinking it'd be a lot larger than that.

我以为它会比那大得多。

Lenny Rachitsky: And I imagine the largest percent is engineers?

Lenny Rachitsky：我想比例最大的是工程师？

Michael Truell: Yeah.

迈克尔·特鲁尔：是的。

To be clear, a big part of the work ahead of us is building a group of people that is bigger, and awesome, and can continue to make the product better, and the service we give to customers better.

需要明确的是，我们面前的工作的很大一部分是建立一支规模更大、更出色的团队，能够继续改进产品，改进我们为客户提供的服务。

And so you don't plan to stay that small for longer, wouldn't hope so.

所以你不打算长期保持这么小的规模，也不希望如此。

But part of the reason that that number is small is, the percentage of engineering and research and design is very high within the company, and so many software companies when they have roughly 40 engineers would be over 100 people, because there's lots of operational work, and often, they're very, very sales-led from the get-go, and that's just quite labor-intensive.

但这个数字很小的部分原因是，公司内部工程、研究和设计的比例非常高，很多软件公司在拥有大约 40 名工程师时，其数量会超过 100 人，因为有大量的运营工作，而且通常，他们从一开始就非常非常以销售为主导，这相当劳动密集型。

And here, we started from a place of being incredibly lean in product-led, and we now serve lots of our market customers, and it built that out, but there's much more to do there.

在这里，我们从以产品为主导的极其精益的地方开始，现在我们为许多市场客户提供服务，并且它已经建立了这一点，但那里还有很多事情要做。

Lenny Rachitsky: A question I wanted to ask you, there's so much happening in AI, there's things launching every...

Lenny Rachitsky：我想问你一个问题，人工智能领域发生了很多事情，每一次都会推出一些东西......

There's newsletters, many newsletters, whose entire function is to tell you what is happening in AI every single day.

有时事通讯，很多时事通讯，其全部功能就是告诉你人工智能每天都发生什么。

Running a company that's at the center, the white-hot center of this space, how do you stay focused, and how do you help your team stay focused, and heads down, and just build and not get distracted by all these shiny things?

经营一家位于中心的公司，这个领域的白热化中心，你如何保持专注，如何帮助你的团队保持专注，低头，只做建设，而不是被所有这些闪亮的东西分散注意力？

Michael Truell: I think hiring is a big part of it, and if you get people with the right attitude.

Michael Truell：我认为招聘是其中很重要的一部分，如果你找到态度正确的人的话。

All of this should be asterisked in, I think we're doing well there, I think that we'd probably be doing better there too, and it's something that we should probably talk even more about as a company.

所有这些都应该加星号，我认为我们在那里做得很好，我认为我们可能在那里做得更好，这是我们作为一家公司应该更多地谈论的事情。

But I think that hiring people with the right disposition, people who are less focused on external validation, more focused on building something really great, more focused on doing really high quality work, and people who are just generally level-headed, and maybe the highs aren't very high, the lows aren't very low.

但我认为，雇用具有正确性情的人，不太关注外部验证的人，更专注于构建真正伟大的东西，更专注于做真正高质量的工作的人，以及通常头脑冷静的人，也许高潮不是很高，低谷也不是很低。

I think hiring can get you through a lot here, and I think that's actually a learning throughout the company, is that for any...

我认为招聘可以让你在这里经历很多事情，我认为这实际上是整个公司的一种学习，对于任何......

You need process, you need hierarchy, you need lots of things, but for any kind of organizational tool that you're introducing into a company, the result you're looking to get from that tool also...

你需要流程，你需要层次结构，你需要很多东西，但是对于你引入公司的任何类型的组织工具，你希望从该工具中获得的结果也......

You can go pretty far on hiring people with the right behaviors that you want to resolve from that for organizational thing.

您可以在雇用具有正确行为的人员方面走得更远，而您希望从组织问题中解决这些问题。

Michael Truell: And the specific example that comes to mind is, we've been able to get away with not a ton of process yet on the engineering front, and I think we need a little bit more process, but for our size, not a ton of process, by hiring people who I think are really excellent.

Michael Truell：我想到的具体例子是，我们在工程方面已经能够摆脱大量的流程，而且我认为我们需要更多的流程，但就我们的规模而言，通过雇用我认为非常优秀的人，不需要太多的流程。

One is hiring people that are level-headed.

一是雇用头脑冷静的人。

I think two is just talking about it a lot.

我认为两个人只是谈论了很多。

I think three is hopefully leading by example.

我认为三个有望以身作则。

And for us personally, we've since 2021, 2022 been professionally working on this, and been working on AI, and we've just seen a sea change of the comings and goings of various technologies and ideas of...

对于我们个人来说，我们自 2021 年、2022 年以来一直在专业地致力于此，并一直致力于人工智能，我们刚刚看到各种技术和想法的来来去去发生了翻天覆地的变化……

If you're to transport yourself back to end of 2021, beginning of 2022, this is GPT-3, Instruct GPT doesn't exist, there's no Dolly, there's no stable diffusion.

如果你要把自己传送到2021年底2022年初，这就是GPT-3，指示GPT不存在，没有Dolly，没有稳定的扩散。

And then we've gone through all of those image technologies existing, ChatGPT and that rise, and GPT-4, all of these new models, all these different modalities, all the video stuff, and only a very small number of these things really kind of affects the business.

然后我们回顾了所有现有的图像技术、ChatGPT 和兴起的 GPT-4、所有这些新模型、所有这些不同的模式、所有视频内容，其中只有极少数真正对业务产生影响。

Michael Truell: So I think we've kind of just built up a little bit of an immune system, and know when an event comes around that actually is really going to matter for us.

Michael Truell：所以我认为我们刚刚建立了一点免疫系统，并且知道何时发生对我们来说真正重要的事件。

This dynamic too of there being lots, and lots, and lots of chatter, but then maybe only a few things that really matter, I think has been mirrored in AI over the last decade, where there have been so many papers on deep learning in academia, so many papers on AI in academia, then the amazing thing is there are really a lot of...

这种动态也有很多、很多、很多的讨论，但也许只有几件真正重要的事情，我认为在过去的十年里已经反映在人工智能中，学术界有很多关于深度学习的论文，学术界有很多关于人工智能的论文，然后令人惊奇的是真的有很多......

A lot the progress of AI can be attributed to some very simple elegant ideas that have stayed around, and the vast majority of ideas that have been put out there haven't had staying power, and haven't mattered a ton.

人工智能的进步在很大程度上可以归因于一些非常简单、优雅的想法，这些想法一直存在，而绝大多数已经提出的想法没有持久力，也没有多大影响。

And so the dynamic is a little bit mirrored in the evolution of deep learning as a field overall.

因此，这种动态在深度学习作为一个整体领域的演变中有所体现。

Lenny Rachitsky: Last question.

莱尼·拉奇茨基：最后一个问题。

What do you think people still most misunderstand, or maybe don't fully grasp about where things are heading with AI in building in the way the world will change?

您认为人们仍然最容易误解什么，或者可能没有完全理解人工智能在改变世界方面的发展方向？

Michael Truell: People are still a little bit occupied too much, either end of a spectrum of it's all going to happen very fast, and this is all bluster, and hype, and snake well, and I think we're in the middle of a technology shift that's going to be incredibly consequential.

迈克尔·特鲁尔：人们仍然有点忙得不可开交，这一切都将发生得非常快，这一切都是咆哮、炒作和蛇行，我认为我们正处于一场技术变革之中，这将产生令人难以置信的后果。

I think it's going to be more consequential than the internet, I think it's going to be more consequential than any shift in tech that we've seen since the advent of computers.

我认为它将比互联网更重要，我认为它将比计算机出现以来我们所看到的任何技术变革都更重要。

And I think it's going to take a while, and I think it's going to be a multi-decade thing, and I think many different groups will be consequential in pushing it forward.

我认为这需要一段时间，而且我认为这将是一个数十年的事情，我认为许多不同的团体将在推动它向前发展方面发挥重要作用。

Michael Truell: And to get to a world where computers can increasingly do more, and more, and more for us, there's all of these independent problems that need to be knocked down, and progress needs to be made on them, and some of those are on the science side of things of getting these models to understand different types of data, be faster, cheaper, smarter, conform to the modalities that we care about, take actions in the real world.

Michael Truell：为了进入一个计算机能够越来越多地为我们做更多事情的世界，所有这些独立的问题都需要解决，并且需要在这些问题上取得进展，其中一些是在科学方面，让这些模型理解不同类型的数据，更快、更便宜、更智能，符合我们关心的模式，在现实世界中采取行动。

And then some of it's on how we're going to work with them, and what's the experience that a human should actually be seeing and controlling on a computer, and working with these things.

其中一些是关于我们将如何与它们合作，以及人类在计算机上实际看到和控制以及使用这些东西应该是什么样的体验。

Michael Truell: But I think it's going to take decades.

迈克尔·特鲁尔：但我认为这需要几十年的时间。

I think that there's going to be lots of amazing work to do.

我认为还有很多令人惊奇的工作要做。

I think that also, one of the most...

我认为这也是最...

A pattern of a group that I think will be especially important here, not to talk our own book, but I think is the company that works on automating and augmenting a particular area of knowledge work, builds both the technology under the surface for that, integrating the best parts from providers, sometimes doing it in-house, and then also builds the product experience for that.

我认为这里特别重要的一个群体模式，不是谈论我们自己的书，而是致力于自动化和增强特定知识工作领域的公司，为此构建表面下的技术，集成提供商的最佳部件，有时在内部进行，然后还为此构建产品体验。

I think people who do that, and...

我认为这样做的人...

We're trying to do it in software, people do that in other areas, I think those folks will be really, really, really consequential.

我们正在尝试在软件中做到这一点，人们在其他领域也这样做，我认为这些人将非常非常重要。

Not just for the end value that users see, but then I think as they get to scale, they'll be really important for pushing forward the technology, because I think they'll be able to build...

不仅仅是为了用户看到的最终价值，而且我认为随着他们规模的扩大，他们对于推动技术发展将非常重要，因为我认为他们将能够构建......

The most successful of them will be able to build very, very big businesses.

他们中最成功的人将能够建立非常非常大的企业。

So, excited to see the rise of other companies like that in other areas.

因此，很高兴看到其他公司在其他领域的崛起。

Lenny Rachitsky: I know you guys are hiring.

Lenny Rachitsky：我知道你们正在招聘。

For folks that are interested in, "Hey, I want to go work here, and build this sort of stuff." What kind of roles are you looking for right now?

对于那些有兴趣的人，“嘿，我想在这里工作，建造这类东西。”您现在正在寻找什么样的角色？

Anyone specifically you're trying...

您具体正在尝试的任何人...

Any roles you're most excited about filling ASAP?

您最希望尽快填补哪些职位？

What should people know if they're curious?

如果人们好奇的话应该知道什么？

Michael Truell: There are so many things that this group of people need to do that we are not get equipped to do.

Michael Truell：这群人需要做很多事情，但我们没有能力去做。

Generic across the board, first of all, and so if you don't think we have a role for something, maybe you should reach out, that won't actually be the case.

首先，全面通用，因此，如果您认为我们在某件事上没有作用，也许您应该伸出援手，但实际上情况并非如此。

And maybe we can actually learn from you, and decide that we need something that we weren't yet aware of.

也许我们实际上可以向您学习，并决定我们需要一些我们尚未意识到的东西。

But by and large, I think that two of the most important things for us to do this year are have the best product in the space, and then grow it.

但总的来说，我认为今年我们要做的最重要的两件事是拥有该领域最好的产品，然后发展它。

And we're kind of in this land grab mode, where almost everyone in the world is either using no tool like ours, or they're using one that's maybe developing less quickly.

我们正处于这种抢地模式，世界上几乎每个人都没有使用像我们这样的工具，或者他们正在使用可能发展较慢的工具。

So growing Cursor too is a big goal, and I would say, especially always on the hunt for folks who...

因此，增长 Cursor 也是一个很大的目标，我想说，尤其是一直在寻找那些......

Excellent engineers, designers, researchers, but then folks all across the business side too.

优秀的工程师、设计师、研究人员，还有业务方面的人们。

Lenny Rachitsky: I can't help but ask this question now that you talk about engineers, there's this question of just, "AI's going to write all our code." But everyone's still hiring engineers like crazy.

Lenny Rachitsky：既然你谈论工程师，我就忍不住问这个问题，就是“人工智能将编写我们所有的代码”。但每个人仍在疯狂地招聘工程师。

All the foundational models, so many open roles.

所有的基础模型，如此多的开放角色。

Michael Truell: Yeah.

迈克尔·特鲁尔：是的。

We're not out there tooting the horn of, people can learn to code.

我们并不是在吹响人们可以学习编码的号角。

Lenny Rachitsky: Do you think there's going to be an inflection point of engineering roles start to slow down?

Lenny Rachitsky：您认为工程角色的拐点会开始放缓吗？

I know this is a big question, but just...

我知道这是一个大问题，但只是......

Do you see engineers being more and more needed across all these companies, or do you think at some point there's all these Cursor agents running building for us?

您是否认为所有这些公司越来越需要工程师，或者您是否认为在某个时候所有这些 Cursor 代理都会为我们运行构建？

Michael Truell: Again, we have the view that there's this both long messy middle of it not jumping to a, just you step back, and you ask for all your stuff to be done, and you have your engineering department.

Michael Truell：我们再次认为，这中间有一个又长又乱的中间部分，不要跳到a，只是你退后一步，你要求完成所有的事情，你有你的工程部门。

And very much, you want to evolve from programming as it exists today, we want humans to be in the driver's seat, and we think even in the end state, that's giving folks control over everything is really important, and you will need professionals to do that, and decide what the software looks like.

非常重要的是，你希望从当今存在的编程中发展出来，我们希望人类占据主导地位，我们认为即使在最终状态，让人们控制一切也非常重要，你将需要专业人员来做到这一点，并决定软件的外观。

Michael Truell: So both I think that, yes, engineers are definitely needed.

Michael Truell：所以我认为，是的，工程师是绝对需要的。

I think that engineers will be able to do much more.

我认为工程师将能够做更多的事情。

I think the demand for software is very lasting, which is not the most novel thing, but I think it's kind of crazy to think about how expensive and labor-intensive it is to build things that are pretty simple and easy to specify, or it would look like it to the outside observer, and just how hard those things are to do right now.

我认为对软件的需求是非常持久的，这不是最新颖的事情，但我认为，考虑构建非常简单且易于指定的东西是多么昂贵和劳动密集型，或者在外部观察者看来是这样的，以及这些事情现在要做起来有多么困难，这有点疯狂。

Michael Truell: All of the stuff that exists right now that's justified by the cost and demand that we have now, if you could bring that down by , I think you would have tons, and tons, and tons of more stuff that we could do in our computers, tons more tools.

迈克尔·特鲁尔：现在存在的所有东西都是由我们现在的成本和需求证明的，如果你能把它降低到 ，我认为你将拥有大量、大量、大量我们可以在计算机中完成的更多东西，更多的工具。

And I've felt this, where...

我也感受到了这一点，哪里...

One of my early jobs actually was working for a biotechnology company, and it was building internal tools for them, and the off-the-shelf tools that existed were horrible, and did not fit their use case at all.

我早期的工作之一实际上是在一家生物技术公司工作，它正在为他们构建内部工具，而现有的现成工具很糟糕，根本不适合他们的用例。

And then the internal tools I was building, there was definitely a ton of demand there for things that could be built, and that far outstripped just the things that I could build in the time that I was with them.

然后我正在构建的内部工具，对可以构建的东西肯定有大量的需求，这远远超出了我在与他们在一起的时间里可以构建的东西。

Michael Truell: The physics of working on computers are so great, you should be able to basically just move everything around, do everything that you want to do.

Michael Truell：在计算机上工作的物理学是如此伟大，你基本上应该能够移动所有东西，做你想做的一切。

There's still so much friction, I think that there's much more demand for software than what we can build today with things costing like a blockbuster movie to make simple productivity software.

仍然存在很多摩擦，我认为对软件的需求比我们今天可以用像大片一样制作简单生产力软件的成本来构建的软件要多得多。

And so I think long into the future, yes, there will actually be more demand for engineers.

所以我认为，在未来很长一段时间内，对工程师的需求实际上会更多。

Lenny Rachitsky: Is there anything that we didn't cover that you wanted to mention?

Lenny Rachitsky：还有什么我们没有提及但您想提及的吗？

Any last nugget wisdom you wanted to leave listeners with?

您最后想向听众传达什么宝贵的智慧吗？

You could also say no, because we've done a lot.

你也可以说不，因为我们已经做了很多。

Michael Truell: We think a lot about how you set up a team to be able to make new stuff, in addition to continuing to improve the stuff that you have right now.

Michael Truell：我们思考了很多关于如何建立一个团队来创造新的东西，以及继续改进你现在拥有的东西。

And I think if we were to be successful, IDE is going to have to change a ton, looks like is going to have to change a ton going into the future.

我认为如果我们想要成功，IDE 就必须进行大量改变，看起来未来也必须进行大量改变。

And if you look around, the companies we respect, there are definitely examples of companies that have continued to really ride the wave of many leapfrogs, and continue to actually push the frontier.

如果你环顾四周，我们尊重的公司中肯定有一些公司的例子，它们继续真正地驾驭着许多跨越式的浪潮，并继续实际推动前沿。

But they're kind of rare too, it's a hard thing to do.

但它们也很罕见，这是一件很难做到的事情。

So part of that is just kind of thinking about the thing, and trying to reflect on it in our good days, and the first principle side of things, part of it's also trying to get in and study past examples of greatness here, and that's something that we think about a lot too.

因此，其中一部分只是思考这件事，并试图在我们美好的日子里反思它，以及事情的首要原则方面，一部分也试图进入并研究过去伟大的例子，这也是我们思考很多的事情。

Lenny Rachitsky: Yeah.

莱尼·拉奇茨基：是的。

Yeah.

是的。

Before we started recording, you had all these books behind you, and I was like, "What's that over there?" It's the history of some old computer company that was influential in a lot of ways that I've never heard of.

在我们开始录音之前，你身后有所有这些书，我当时想，“那边那是什么？”这是一家老牌计算机公司的历史，该公司在很多方面具有我从未听说过的影响力。

And I think that says a lot about you of, where a lot of this innovation comes from, is studying the past, and study history, and what's worked and what hasn't.

我认为这说明了很多关于你的事情，很多创新来自于研究过去，研究历史，以及哪些有效，哪些无效。

Lenny Rachitsky: Okay.

莱尼·拉奇茨基：好的。

Where can folks find you online if they want to reach out and maybe apply?

如果人们想联系并申请职位，可以在哪里找到您？

You said that there may be roles they may not even be aware of, where do they go find that, and then how can listeners be useful to you?

你说可能有些角色他们可能都不知道，他们去哪里找到这个角色，那么听众对你有什么用处呢？

Michael Truell: Yeah.

迈克尔·特鲁尔：是的。

If folks are interested in working on this stuff, would love to speak, they can find...

如果人们对这方面的工作感兴趣，愿意发言，他们可以找到......

If they go to cursor.com, they can kind of both find the product and find out how to reach us.

如果他们访问cursor.com，他们既可以找到产品，也可以找到如何联系我们。

Lenny Rachitsky: Easy.

莱尼·拉奇茨基：简单。

Michael, thank you so much for being here.

迈克尔，非常感谢你来到这里。

This was incredible.

这太不可思议了。

Bye, everyone.: Thank you so much for listening.

再见，大家：非常感谢您的聆听。

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如果您发现这很有价值，您可以在 Apple Podcasts、Spotify 或您最喜欢的播客应用程序上订阅该节目。

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您可以在 lennyspodcast.com 上找到所有过去的剧集或了解有关该节目的更多信息。

See you in the next episode.

下一集见。